{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/CoreTheGreat/HBPU-Machine-Learning-Course/blob/main/ML_Chapter3_Classification.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "lPboLx_o0UxI"
   },
   "source": [
    "# 第三章：分类\n",
    "湖北理工学院《机器学习》课程资料\n",
    "\n",
    "作者：李辉楚吴\n",
    "\n",
    "笔记内容概述: 敏感性 Specificity、特异性 Sensitivity、ROC曲线\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Ifpm7Sql4U09"
   },
   "source": [
    "## Step 1: 数据准备\n",
    "\n",
    "使用make_moons生成虚拟数据构建分类任务"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "sM-ziKb94S9_",
    "outputId": "9a8bd59b-1ed4-47e3-e118-cee1849a610a"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.datasets import make_moons\n",
    "from sklearn.model_selection import train_test_split\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "label_size = 18 # Label size\n",
    "ticklabel_size = 14 # Tick label size\n",
    "\n",
    "# Generate moon-shaped data\n",
    "X, Y = make_moons(n_samples=1000, noise=0.4, random_state=42)\n",
    "\n",
    "# Split X and Y into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.3, random_state=42)\n",
    "\n",
    "# Plot the data\n",
    "fig, ax = plt.subplots(figsize=(10, 8))\n",
    "ax.scatter(X_train[y_train == 1, 0], X_train[y_train == 1, 1], color='red', label='Positive - Train')\n",
    "ax.scatter(X_test[y_test == 1, 0], X_test[y_test == 1, 1], color='orange', label='Positive - Test')\n",
    "ax.scatter(X_train[y_train == 0, 0], X_train[y_train == 0, 1], color='blue', label='Negative - Train')\n",
    "ax.scatter(X_test[y_test == 0, 0], X_test[y_test == 0, 1], color='green', label='Negative - Test')\n",
    "ax.set_xlabel('Feature 1', fontsize=label_size)\n",
    "ax.set_ylabel('Feature 2', fontsize=label_size)\n",
    "\n",
    "ax.tick_params(axis='both', which='major', labelsize=ticklabel_size)\n",
    "\n",
    "# Set legend fontsize\n",
    "plt.legend(prop={'size': 14})\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 2: SVM进行分类，输出概率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "BWPSDyOq5qOO",
    "outputId": "9aed06f2-67a9-4a6f-f00c-d91554c3a260"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Support vector machine trained successfully...\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "# Model Definition\n",
    "mdl_svm = SVC(probability=True)\n",
    "\n",
    "mdl_svm.fit(X_train, y_train) # Support Vector machine\n",
    "print('Support vector machine trained successfully...')\n",
    "\n",
    "# Predict probabilities\n",
    "y_proba_svm = mdl_svm.predict_proba(X_test)[:, 1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "BtGNbqlSKnC-"
   },
   "source": [
    "## Step 3: 生成混淆矩阵，计算敏感性和特异性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "When threshold = 0.00 - Sensitivity: 1.0000, Specificity: 0.0000\n",
      "When threshold = 0.01 - Sensitivity: 1.0000, Specificity: 0.0000\n",
      "When threshold = 0.02 - Sensitivity: 1.0000, Specificity: 0.0000\n",
      "When threshold = 0.03 - Sensitivity: 1.0000, Specificity: 0.0000\n",
      "When threshold = 0.04 - Sensitivity: 1.0000, Specificity: 0.0705\n",
      "When threshold = 0.05 - Sensitivity: 1.0000, Specificity: 0.1410\n",
      "When threshold = 0.06 - Sensitivity: 0.9931, Specificity: 0.2692\n",
      "When threshold = 0.07 - Sensitivity: 0.9931, Specificity: 0.3846\n",
      "When threshold = 0.08 - Sensitivity: 0.9861, Specificity: 0.4679\n",
      "When threshold = 0.09 - Sensitivity: 0.9792, Specificity: 0.5256\n",
      "When threshold = 0.10 - Sensitivity: 0.9792, Specificity: 0.5513\n",
      "When threshold = 0.11 - Sensitivity: 0.9792, Specificity: 0.6090\n",
      "When threshold = 0.12 - Sensitivity: 0.9792, Specificity: 0.6282\n",
      "When threshold = 0.13 - Sensitivity: 0.9792, Specificity: 0.6603\n",
      "When threshold = 0.14 - Sensitivity: 0.9653, Specificity: 0.6795\n",
      "When threshold = 0.15 - Sensitivity: 0.9583, Specificity: 0.6987\n",
      "When threshold = 0.16 - Sensitivity: 0.9583, Specificity: 0.7179\n",
      "When threshold = 0.17 - Sensitivity: 0.9583, Specificity: 0.7244\n",
      "When threshold = 0.18 - Sensitivity: 0.9583, Specificity: 0.7372\n",
      "When threshold = 0.19 - Sensitivity: 0.9583, Specificity: 0.7500\n",
      "When threshold = 0.20 - Sensitivity: 0.9583, Specificity: 0.7564\n",
      "When threshold = 0.21 - Sensitivity: 0.9444, Specificity: 0.7692\n",
      "When threshold = 0.22 - Sensitivity: 0.9375, Specificity: 0.7692\n",
      "When threshold = 0.23 - Sensitivity: 0.9306, Specificity: 0.7756\n",
      "When threshold = 0.24 - Sensitivity: 0.9306, Specificity: 0.7756\n",
      "When threshold = 0.25 - Sensitivity: 0.9236, Specificity: 0.7756\n",
      "When threshold = 0.26 - Sensitivity: 0.9236, Specificity: 0.7949\n",
      "When threshold = 0.27 - Sensitivity: 0.9097, Specificity: 0.7949\n",
      "When threshold = 0.28 - Sensitivity: 0.9097, Specificity: 0.7949\n",
      "When threshold = 0.29 - Sensitivity: 0.9097, Specificity: 0.8013\n",
      "When threshold = 0.30 - Sensitivity: 0.9028, Specificity: 0.8077\n",
      "When threshold = 0.31 - Sensitivity: 0.8958, Specificity: 0.8077\n",
      "When threshold = 0.32 - Sensitivity: 0.8958, Specificity: 0.8141\n",
      "When threshold = 0.33 - Sensitivity: 0.8958, Specificity: 0.8141\n",
      "When threshold = 0.34 - Sensitivity: 0.8819, Specificity: 0.8205\n",
      "When threshold = 0.35 - Sensitivity: 0.8819, Specificity: 0.8205\n",
      "When threshold = 0.36 - Sensitivity: 0.8750, Specificity: 0.8397\n",
      "When threshold = 0.37 - Sensitivity: 0.8750, Specificity: 0.8397\n",
      "When threshold = 0.38 - Sensitivity: 0.8681, Specificity: 0.8462\n",
      "When threshold = 0.39 - Sensitivity: 0.8681, Specificity: 0.8526\n",
      "When threshold = 0.40 - Sensitivity: 0.8542, Specificity: 0.8654\n",
      "When threshold = 0.41 - Sensitivity: 0.8472, Specificity: 0.8654\n",
      "When threshold = 0.42 - Sensitivity: 0.8472, Specificity: 0.8718\n",
      "When threshold = 0.43 - Sensitivity: 0.8472, Specificity: 0.8718\n",
      "When threshold = 0.44 - Sensitivity: 0.8472, Specificity: 0.8782\n",
      "When threshold = 0.45 - Sensitivity: 0.8472, Specificity: 0.8782\n",
      "When threshold = 0.46 - Sensitivity: 0.8472, Specificity: 0.8782\n",
      "When threshold = 0.47 - Sensitivity: 0.8403, Specificity: 0.8782\n",
      "When threshold = 0.48 - Sensitivity: 0.8403, Specificity: 0.8782\n",
      "When threshold = 0.49 - Sensitivity: 0.8333, Specificity: 0.8782\n",
      "When threshold = 0.51 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.52 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.53 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.54 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.55 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.56 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.57 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.58 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.59 - Sensitivity: 0.8125, Specificity: 0.8782\n",
      "When threshold = 0.60 - Sensitivity: 0.8056, Specificity: 0.8910\n",
      "When threshold = 0.61 - Sensitivity: 0.8056, Specificity: 0.8910\n",
      "When threshold = 0.62 - Sensitivity: 0.7986, Specificity: 0.8910\n",
      "When threshold = 0.63 - Sensitivity: 0.7986, Specificity: 0.8910\n",
      "When threshold = 0.64 - Sensitivity: 0.7986, Specificity: 0.8974\n",
      "When threshold = 0.65 - Sensitivity: 0.7917, Specificity: 0.8974\n",
      "When threshold = 0.66 - Sensitivity: 0.7917, Specificity: 0.9038\n",
      "When threshold = 0.67 - Sensitivity: 0.7847, Specificity: 0.9038\n",
      "When threshold = 0.68 - Sensitivity: 0.7569, Specificity: 0.9038\n",
      "When threshold = 0.69 - Sensitivity: 0.7569, Specificity: 0.9038\n",
      "When threshold = 0.70 - Sensitivity: 0.7569, Specificity: 0.9038\n",
      "When threshold = 0.71 - Sensitivity: 0.7569, Specificity: 0.9103\n",
      "When threshold = 0.72 - Sensitivity: 0.7569, Specificity: 0.9103\n",
      "When threshold = 0.73 - Sensitivity: 0.7500, Specificity: 0.9103\n",
      "When threshold = 0.74 - Sensitivity: 0.7500, Specificity: 0.9103\n",
      "When threshold = 0.75 - Sensitivity: 0.7361, Specificity: 0.9167\n",
      "When threshold = 0.76 - Sensitivity: 0.7153, Specificity: 0.9167\n",
      "When threshold = 0.77 - Sensitivity: 0.7083, Specificity: 0.9295\n",
      "When threshold = 0.78 - Sensitivity: 0.7083, Specificity: 0.9359\n",
      "When threshold = 0.79 - Sensitivity: 0.7014, Specificity: 0.9423\n",
      "When threshold = 0.80 - Sensitivity: 0.6944, Specificity: 0.9423\n",
      "When threshold = 0.81 - Sensitivity: 0.6875, Specificity: 0.9423\n",
      "When threshold = 0.82 - Sensitivity: 0.6806, Specificity: 0.9487\n",
      "When threshold = 0.83 - Sensitivity: 0.6806, Specificity: 0.9615\n",
      "When threshold = 0.84 - Sensitivity: 0.6528, Specificity: 0.9615\n",
      "When threshold = 0.85 - Sensitivity: 0.6319, Specificity: 0.9679\n",
      "When threshold = 0.86 - Sensitivity: 0.6181, Specificity: 0.9744\n",
      "When threshold = 0.87 - Sensitivity: 0.6042, Specificity: 0.9744\n",
      "When threshold = 0.88 - Sensitivity: 0.5764, Specificity: 0.9744\n",
      "When threshold = 0.89 - Sensitivity: 0.5556, Specificity: 0.9808\n",
      "When threshold = 0.90 - Sensitivity: 0.5000, Specificity: 0.9936\n",
      "When threshold = 0.91 - Sensitivity: 0.4583, Specificity: 1.0000\n",
      "When threshold = 0.92 - Sensitivity: 0.3750, Specificity: 1.0000\n",
      "When threshold = 0.93 - Sensitivity: 0.3056, Specificity: 1.0000\n",
      "When threshold = 0.94 - Sensitivity: 0.2361, Specificity: 1.0000\n",
      "When threshold = 0.95 - Sensitivity: 0.1806, Specificity: 1.0000\n",
      "When threshold = 0.96 - Sensitivity: 0.0972, Specificity: 1.0000\n",
      "When threshold = 0.97 - Sensitivity: 0.0347, Specificity: 1.0000\n",
      "When threshold = 0.98 - Sensitivity: 0.0000, Specificity: 1.0000\n",
      "When threshold = 0.99 - Sensitivity: 0.0000, Specificity: 1.0000\n",
      "When threshold = 1.00 - Sensitivity: 0.0000, Specificity: 1.0000\n"
     ]
    }
   ],
   "source": [
    "def confusion_matrix(y_pred, y):\n",
    "    '''\n",
    "    y_pred - predict classes\n",
    "    y - actual classes\n",
    "    '''\n",
    "    # Get the number of classes\n",
    "    n_classes = len(np.unique(y))\n",
    "    \n",
    "    # Initialize the confusion matrix with zeros\n",
    "    cm = np.zeros((n_classes, n_classes))\n",
    "    \n",
    "    # Fill the confusion matrix\n",
    "    for pred, actual in zip(y_pred, y):\n",
    "        cm[pred][actual] += 1\n",
    "    \n",
    "    return cm\n",
    "\n",
    "def get_prediction_from_proba(y_proba, threshold=0.5):\n",
    "    '''\n",
    "    y_proba - predict probabilities\n",
    "    threshold - threshold of probability\n",
    "    \n",
    "    y_pred - predict classes, y_proba > threshold is positive, otherwise negative\n",
    "    '''\n",
    "    y_pred = np.where(y_proba > threshold, 1, 0)\n",
    "    return y_pred\n",
    "\n",
    "def get_sensitivity_specificity(y_proba, y, threshold=0.5):\n",
    "    '''\n",
    "    Compute sensitivity and specificity of binary classification\n",
    "    y_pred - predict classes\n",
    "    y - actual classes\n",
    "    threshold - threshold of probability\n",
    "    '''\n",
    "    epsilon = 1e-10\n",
    "    \n",
    "    # Get the confusion matrix\n",
    "    y_pred = get_prediction_from_proba(y_proba, threshold)\n",
    "    cm = confusion_matrix(y_pred, y)\n",
    "    \n",
    "    # Compute sensitivity and specificity\n",
    "    sensitivity = cm[1, 1] / (cm[1, 1] + cm[0, 1] + epsilon)\n",
    "    specificity = cm[0, 0] / (cm[0, 0] + cm[1, 0] + epsilon)\n",
    "    \n",
    "    return sensitivity, specificity\n",
    "\n",
    "# Get predictions from probabilities\n",
    "sen_spec_svm = []\n",
    "for threshold in np.linspace(0, 1, 100):\n",
    "    sensitivity, specificity = get_sensitivity_specificity(y_proba_svm, y_test, threshold)\n",
    "    print(f\"When threshold = {threshold:0.2f} - Sensitivity: {sensitivity:.4f}, Specificity: {specificity:.4f}\")\n",
    "    sen_spec_svm.append([sensitivity, specificity])\n",
    "\n",
    "# Convert to numpy array\n",
    "sen_spec_svm = np.array(sen_spec_svm)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 4: 绘制Specificity-Sensitivity曲线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Use sen_spec_svm to draw specificity-sensitivity curve\n",
    "fig, ax = plt.subplots(figsize=(8, 6))\n",
    "ax.plot(sen_spec_svm[:, 1], sen_spec_svm[:, 0], marker='.', color='tab:blue', label='SVM Model')\n",
    "ax.set_xlabel('Specificity', fontsize=label_size)\n",
    "ax.set_ylabel('Sensitivity', fontsize=label_size)\n",
    "ax.tick_params(axis='both', which='major', labelsize=ticklabel_size)\n",
    "\n",
    "# Set axis limits\n",
    "ax.set_xlim([0, 1.01])\n",
    "ax.set_ylim([0, 1.01])\n",
    "\n",
    "# Save the figure\n",
    "plt.savefig('Specificity_Sensitivity_Curve.png', dpi=300)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtUAAAIfCAYAAAC/wCC5AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8fJSN1AAAACXBIWXMAAA9hAAAPYQGoP6dpAACsm0lEQVR4nOzdd3hUZd7/8feZSe8JCYQekN5r6CWANMW2WFF0XXR13aKuu5ZdRdR9dNVdd33097iuLlZsWNAVBOmd0EGadEJCSEJ6nczM+f0RMhJCSSZlMsnndV25YO5z5pwviOHDPff53oZpmiYiIiIiIuI2i6cLEBERERHxdgrVIiIiIiI1pFAtIiIiIlJDCtUiIiIiIjWkUC0iIiIiUkMK1SIiIiIiNaRQLSIiIiJSQwrVIiIiIiI1pFAtIiIiIlJDCtUiIiIiIjXkNaH6gw8+4Je//CWDBg3C398fwzB45513qn0dp9PJa6+9Rp8+fQgMDCQmJoabbrqJgwcP1n7RIiIiItIkGKZpmp4uoiri4uI4fvw40dHRBAcHc/z4cebOnctdd91Vrevce++9/Pvf/6ZHjx5cddVVnD59mk8++YSAgADWr19Pjx49qnwtp9NJSkoKoaGhGIZRzV+RiIiIiNQ10zTJy8ujVatWWCx1OJ9seonvv//ePHbsmGmapvn888+bgDl37txqXWP58uUmYI4aNcosLi52jS9dutQ0DMMcPXp0ta6XlJRkAvrSl770pS996Utf+mrgX0lJSdXKedXlg5eYMGFCja/x73//G4DnnnsOf39/1/j48eOZNGkS3333HT/++CNdunSp0vVCQ0MBSEpKIiwsrMb1iYiISNNVevo0thNJ+LVri2+LFp4u55K8qdYTn3xC73vvdeW2uuI1obo2rFy5kuDgYEaMGFHpWHmoXrVqVZVDdfmSj7CwMIVqERERcVv2/PmkPTUbnE6wWGj5zBwipk/3dFkX5E21HrpyIkXHjgHU+VLdJhOqCwoKOHXqFL169cJqtVY63rlzZ4BLPrBYUlJCSUmJ63Vubm7tFyoiIiJewTRNKC3FWVSEs7gY8+yPzsIizOKzPy8qwjw75iwuwiwqPjte6Pq5Izubwo0bf7qw08mpPz9J5gcfYvj6eu4XeAFmaSkl+/f/NNCAa7VnZlKanMyJdu3gUN03pGgyoTonJweA8PDwCx4vn2kuP+9Cnn/+eebMmVP7xYmIiFcpTU3Fduw4fnHt8Y2N9XQ5DUpD+b0xTROztNQVdM2iorLwW1RcMfCeHXMF3qKLh9+fQnNhWVAuLgaHo85+DRXCawPXUGs1DYMjV3SE5cvq/F5NJlTXhscff5yHH37Y9To3N5e2bdt6sCIREalv2fPnc8pLPvqub1X9vTk/8LpCanngPTf8ugLvpcOvWVRYdrx8ZriOA2+lX5PFghkQiOkfgOnvj9Ov7EczIADTLwCnv7/rmOkfAP4BZa8D/LHYSwl95w2McxqymYZB3m8fwwyLqLdfQ1UYudmEvvpCg6/VNE18d24h6Jv5DN6UWC/3bDKhunyG+mIz0eVLOS42kw3g7+9f4QFHERFpXEynE2dhIc7cXBx5+TjzcnHk5pX9mJdPaUoymXPfgfJA4XRy6smnyFuxEktgoEdr9zRnURH5y86ZDTxnWQAOe8XAW1RUFrzriWm1ng205wTegLMBtzzwng2/pr//OYE3ACOg7OeGfwAEBEBAIEaA/9kfA1w/Wnx9MQywGIbrx+pwRkVieeUFDKcT02LB+dBjBE25po5+R2rG6WM02FqdTid7t23AdDrp/btHMLdsIOjkiXq5d5MJ1cHBwbRs2ZKjR4/icDgqrasuX0tdvrZaRES8j2m348zPx5GXhzMvD0duHo68XJy5eTjzK7525OeV/ZiXdzZE5+HMz69+2DPNimFSKrjcsgDTxwfT76dZXOc54dc8G36d5T8vD7wBgZj+/j8F3oBA8Pf/KfAGBpX96F87gbc+mFOuwTFoKEZyEmbrthDT3NMlXVRDrbUwP5fEFYvITDsFQLtO3Ql//3McX34Kv723zu/fZEI1wJgxY/j4449Zt24do0ePrnBs8eLFrnNERKT2VWWtrdNmOxuGc8t+dIXjc16fG4Tz838KxHl5OAsKaqVW08cXZ3BI2VdQMGb5j1YrQWuXc24kMw2DvJtmYgaH1Mq9vZVRkE/op+9VXhbwm8cwY5pDQCAElgVgbwu89SamednvlTdoYLWmHDvE1jXfU2orwcfXjwGjJhAeFV12cMLkeqmhUYbqjIwMMjIyiI6OJjo62jV+77338vHHH/PnP/+ZpUuX4ufnB8CyZctYvHgxo0ePrnI7PRERuTiztBR7Zib2jAwcmZnkLvqOnC+/dC2bCOjdC2t4hCsol4dm85wOSzXh9A9wBWFnULArIJeNlf1ohoRASCgEh2CEhJZ9hZb93OLvj8ViYLEYWM8Lec5FXzfYj749zdmmtX5vpF45HHZ+SFzL4b07AIiMbkF8wlSCwy6+nLeueM025W+99RZr164FYPfu3Wzbto0RI0bQqVMnAK677jquu+46AJ5++mnmzJnD7Nmzefrppytc55577uGtt96qlW3Kc3NzCQ8PJycnR32qRaTRcxYVYT9zBkdGxk+B+cwZ7BlnsGeewZFxBvuZsi/nJTopVeleQcE4g0JwBge7QrAz+Gw4DgqB4BDMs4GYs+HYck4otvr5YjEMLEYd9aZNT2twH303GPq9kXpimiZrFn1OxqmTAHTuPZCeA4djOW+Jb35eLsN7tKvzvOY1M9Vr167l3XffrTC2bt061q1bB0BcXJwrVF/Kv/71L/r06cO//vUvXn31VUJCQpg2bRp/+ctfNEst0kDUdkuu6lyvobQDq616LvV+0zRx5uVhzziD40wG9jOZ2M9cPCibhYXVurdpseIMD8fpF4Dv6ZRKx/NvuA17t54YwWWh2AgNhZAQrMHBWHx8XKHYpyEuB2hgH303KPq9kXpiGAYduvYmNzODQWMmEdu2g2fr8ZaZ6oZIM9UitS97/nxOPflU2TIBwyB8+s8Ijo93+3oFiYnkzP+8Sterzrn1oab1nP/+wH79sISFuoKy48wZzNLSatVk+vrhCI/EERGJMzzC9XMzIgoioyAiEiOyGZZmUVjCw7FarVjPpONz+/UY5zwAaFosOD78SjOZIlIt9tJSCvKyCY+KcY3ZSorx8w+46Hvqa6ZaoboGFKpFalf+mjUk3VP3T2hLRc7AIJwRkdjDI3GGR+I4+6N5NiQTFYUlshk0i8InOASr1YLVUr3ZY+MC65BNrbUVkWrIyUwncflCbLYSxl8/g4DA4Cq9T8s/RKTJsJ04Qfo/XyX3228vfLxjF5whodW+riU/D78jP1bpetU5tz7UtJ6LvT//upux9+yHERUFUc2wREThExSAxTDwqWZQro6G2oJLRBo+0zQ5un83uzatwulwEBAUTFFBfpVDdX1RqBYRj7Gnp5Pxf2+Q9emnYLcDYELFdmUWC5a/vIzFnRCWnoY547pKyw4ueL3qnFsfalrPRd4fcPMMzwVarbUVkWqylRSzfe0yko+V7SfSok0cg0ZPxD8wyMOVVWbxdAEi0vQ48vJI+8c/ODRxElnz5oHdTlH/eDL+/m/sDz2OaSn71lS+TMDtEBjTvGyZQVWuV51z60NN62lovx4RkWrKTE9l+VfzSD52EMOw0Dt+FMMnXtsgAzVoTXWNaE21SNWUd6DwadWS/KXLOPOvf+E423LN1rk7OXfcS8iQIfhaz/47v7ZbclXneg2tHVhN62lovx4RkSrasnoxJw7uIyg0jPiEqUTFuNeRSQ8qegGFapHLy54/n1NPza609XNpm/bk3PYLAhPG4e+rlWgiIlJRqc3Gvm0b6D5gKL5+/m5fRw8qiohXs51MJve7RaS//LcK4yaQfed9+N54KxEB7n+TFBGRxiX9VBJJhw/Qf8R4DMPA18+PPkPHeLqsKlOoFvES52/icblNQap7vKYbpDiysynYlEjB+vUUbNhA6YkTF3yvAYT17o2pQC0iIoDpdLJvxyb2b98EQFTzlsR16enhqqpPoVrEC1RYQmGxEH7NNeR8/bXrdctn5hAxffpFz7/c8ctd76K1GAbBI0fiyMqieM+esk1GzjKtVmwdOuN36AAG54xbLGXre0VEpMkrKshn88pFZKQmA9C+S0/adPDOHa61proGtKZa6kNpaiqHxo2vtCb5fJbwcAyLBdPpxHn2IcDqHL/Y+ee63HtL28ZR1GcA9r6DsfQfSGB4KD6Lv9GmHyIiUsmpE0fZunoxtpJifHx96T9iPG2v6Fbr99GaahEBIOfbby8bqIHLBuWqBGl3z8+9YQaOa6YT0LIFQdbzgrg2/RARkfP8uGsLP2xeC0BEs+bEJ0whJDzSw1XVjEK1SANlmiaZb79N+t/+XvkYlTdIyX/uFczIKIysTEL+9CCGaVb9+CWud66LXTvoxpsvHZa16YeIiJwjOrY1hmGhY/c+9IofidXq/ZFUm7+INEDOwkJSfv970l7+G5gmxd16VdjEw5w4tdKmHoHxQwjq3JnA+CE4H668gcqljl/qeud+Xezamn0WEZHLKcj76RPQqOYtmTj9TvoOG9soAjVoTXWNaE211KbyjhqGny+pT8+h5McfMa1WMn/+a4Km34Rv1pmKSygut6lHdY978wYpIiLSYNntpezauIoTh/aRcM2thEdF1+v9taZapAm50AYpzogozvzhacLjB2MxjMpLKC63pKK6x6uzREPLOUREpApys86QuHwhudlnAMhIPVnvobq+KFSLeFhpamqlQG0COX9+gch+fTxXmIiIiJtM0+T4j3vYuWElDocd/8AgBo+ZTPPW7TxdWp1RqBbxMNux45W6exhAGKVobZaIiHibUlsJ29ct5+SRAwA0b92OQWMmERAY7OHK6pZCtYiH+cW1B4ul4ky1NkgREREvdfzHvZw8cgDDMOgxcDhd+gzCMIzLv9HLKVSLeJhvbGzZjoZffQWULf0wJ0zWA4AiIuKVrujRl+wzaXTo1ptmLVp5upx6o5Z6Ih5mS04mZ8EC12sDMJZ+B+lpnitKRESkikqKi9i1aTUOux0Aw2Jh0JhJTSpQg2aqRTymaNdu8tetI/e//4XzOlsaTmdZyzrNVouISAOWkZrM5pWLKCrIx3Q66TtsrKdL8hiFahEPSHnscddyD7jwjoZaUy0iIg2V6XRyYNcW9m3bgGmahIRH0r5LD0+X5VEK1SL1rGjX7gqBulx5sNYuhSIi0pAVFRawZdV3pKckAdCuU3f6DU/Ax9fPw5V5lkK1SC0p3xHRL649vrGxFz2vcOvWSmMG4LjjF9B3gHYpFBGRBuvM6RQ2Lv0vJcWFWH186Dd8HO07N+0Z6nIK1SK1oMKOiIZB9P33ETphwgXPtUZFVRozAXPICOimb0wiItJwBQaF4HQ6CI+KJj5hKqERlf9Oa6oM0zS1v4SbcnNzCQ8Pr/O95KVhK01N5dC48ZU2cKkOE3B89LVmqEVEpMEptZXg6+fvep2VkUZYRBRWH++Ym83Py2V4j3Z1nte843dDpAG70I6IAI7QMLjQ+rJSG9a83ApDBqjbh4iINDjJxw6xbc33DBozmZbtOgAQGa2/qy5EoVqkhi62I6LjX+9feOY5PQ3L7ddjaAdFERFpoBx2O7sTV3Nk3y4Aju7f5QrVcmHa/EWkhnxjY2n5zBzXa9MwcD70GJbmLbAYRuWv5i1wPvQYpqXsfz91+xARkYYkLzuTld987ArUXXoPZOiEqz1cVcOnmWoRN53b7SNi+nQyP/qYkj17KLjqegKmXHPJ95pTrsExaGjZkg91+xARkQbi+MG97Fi/Aoe9FP+AQAaOmURsmzhPl+UVaiVU2+120tPTSU9Pp7i4mGbNmhETE6OH96TRqtDtw2IhsE8fSvbsASD4v19g2opx/vGpS18kprnWUIuISIORmXaKrauXABDTsg2DxkwmMDjEw1V5D7dD9apVq/juu+9YtWoVW7duxX52v/dztWzZktGjRzNmzBimT59Os2bNalSsSENQmpr6U6AGcDop2rHDddwAWLIQrpmuFnkiIuI1opq3pEO33gQEhdCt72AMi1YJV0e1Wurl5uby1ltv8eabb3Lw4EEAqvJ2wzDw8/Pjhhtu4P7772fkyJHuV9yAqKVe01K+3MN26hSpjz9+2fMd9/0Oc/qt9VCZiIhI9ZmmybEDP9CyfUcCAoNdY4ZheLiy2tWgWurZ7XZef/11nnvuOTIzMzFNk9DQUOLj4xkyZAj9+/cnOjqaqKgoAgMDyczMJDMzk6NHj7Jp0yY2bdrEgQMH+Oijj/j444+ZPHkyL730Ej16aBZPvEOF5R4XUL7F+LmvzV5966M0ERGRarOVFLNt7VJSjh0i+dhBRky6HsMwGl2grk9VCtU9evTg8OHD+Pj4cM0113D77bczbdo0/Pwuv8f7/fffD8DBgwf54IMPmDdvHosWLWLJkiX85z//4Y477qjZr0CkjlVa7kFZaAYDA7OsHV63nrB3N8bZY+bEqVr6ISIiDdKZ0ylsXrmIwvw8DItFDyLWkiqF6uPHj3PvvffyxBNP0Late710O3fuzJw5c5gzZw6ffPIJzz77LEePHnXrWiL1pWjXbrK/+KLSDLUBOJ58DsIjfuresX8vxg87y2aoFahFRKSBMU2TH3dtYe/W9ZimSXBoOPEJU4mMaeHp0hqFKq2pTkpKcjtMX4xpmqSkpNC6detavW590prqxi3lscfJ+eqrCx4zDQPHvAVqhSciIl6hpLiIzSu/Iy35OABtOnah/4jxFbYfb6wa1Jrq2g7UUPbwojcHamncinbtvmigFhER8TYWi5XCvBysVh/6DBtLXJeeWj9dy7T5i8gFFGzdcsnjhmmWbdyimWoREWmgnE6n6+FDXz8/hoy/CsOwEBapFsd1we0GhOPGjeOTTz6htLS0NusRaRCc+fmXPG5aLGVrqUVERBqgwvw81iycz+E9O1xj4VExCtR1yO1QvXLlSm677TZat27NH//4R1ffahFvZ8/KIvvDeUB5l4+zHT3Kf26x4HzoMa2nFhGRBinl+GGWf/UhZ06nsH/HJkptNk+X1CRUa/OXc91xxx18/vnnFBcXu9bkjB07ll/+8pdcf/31+Pr61mqhDZEeVGycUp74EzlffEFpuw6U/PaPBB7aX9bRo1l02ZKP8m4fIiIiDYjDYeeHzWtds9MR0c2JT5hKSFiER+vytPp6UNHtUA2QnZ3N+++/z1tvvcXu3bvLLmgYNGvWjJ///OfMmjWLzp0711qxDY1CdeOT+dHHnJ4zB4D0518ncvBAD1ckIiJyefm52SQuX0j2mTQAOvXsT6/BI7FYrR6uzPO8IlSfa9OmTbz55pt8+umnFBQUNInZa4XqxuXkw78nb+FCoGyph+PKqfDoU54tSkRE5DJKbSUs/nQutpJi/PwDGDh6Ii3bdfR0WQ2G14Xqcnl5eXz44Yf8+9//Zvv27WU3aaSz1wrV3s1ZXEzRtm0UbNhA3tJl2M7bjMgEHK/9Rxu5iIhIg/fjri2kJh1l0NjJBAWHerqcBsVrQ/W5tm/fzoMPPsiaNWsq9EIcP348jzzyCBMnTqyrW9cLheqGr2jXbgq3biVo4EACevageN9+Cjasp3DDBgq3bsMsKbnk+x33/Q5z+q31VK2IiEjV5GRmYBiGq5uHaZqYponF4nYPikarQW3+Ul1FRUV8/PHHvPnmmyQmJgJl/7GjoqLIzMxk6dKlLFu2jGnTpjFv3jyCgoLqogxp4irtiOjrC+e1gHRERVPUZyD2Fi0J/+Qdzm2Db0LZA4oiIiINhGmaHDvwAzs3riQ4JIyEa2/Dx9fX1Y9aPKdWQ/WOHTt48803mTdvHnl5eZimiY+PD9deey33338/48aNY9u2bbz66qt8+OGHfPPNNzz11FO8/PLLtVmGCIW7dlXeEbG0FKe/P8W9B1LSdyAMjMe/Q0cCfMse4jCz0mDJQgzOBuqJU7X0Q0REGoxSWwnb1y7j5NEfAQgKDcPhsOPTyJ5Z81Y1Xv5RUFDAvHnzePPNN9m2bRtQ9q+odu3acc899zBr1ixatGhR6X0LFy7k6quvpm3bthw/frwmJXiMln94XmlqKrZjx/GLa49vbCylqamUHDzI6ZdewvZj5d7pxbMewHrz7Rf/1/z+vRg/7CyboVagFhGRBiIzPZXNKxZRkJeDYVjoOWg4nXsP1Ox0FTT45R9btmzhzTff5OOPP6agoMC1jmfSpEncf//9XHXVVZf8Dz116lRiYmJITk52twRp4rLnz+fUU7PB6QSLhbCrryL3v9+WvaZstvn85Rw+/QbCpb4BdeuBqTAtIiINhGmaHNqznR82r8V0OgkKCSM+YQpRzVt6ujQ5j9uhOj4+HsMwME2T5s2b84tf/IJ7772X9u3bV/kagYGB1OFzktKIlaamcurJp6D8z4/TSe7X31Q6rzxYazmHiIh4JdMk9cQRTKeTVnGdGDByAn7+AZ6uSi6gRmuqR48ezf33388NN9yAj0/1L7Vu3TrsdntNSpAm6sy77/4UqC/CABy//SPYSrScQ0REvIppmmUPH1osDBozmdSko8R17aXlHg2Y26F67969dOvWrUY3b926dY3eL02PabOR+j//Q/bHn1Q+xnnLPSwWzGEjtaW4iIh4DdPpZP+OREpKiug3LAGAwOAQOnTr7eHK5HLcbmaYlpbGxo0bq3x+YmIiq1evdvd2IpSmpXH8zrvI/vgTTMOgIH4k5tl+nKbFgjlxaoXXzoceU6AWERGvUVSQz5rvvmDf9o0c2buTzPRUT5ck1eB29w+LxULLli2r/KBhhw4dSEpKalTLPdT9o+6Vd/dwFuSTOucZ7GlpOINDyPjdnwgfOxbrmXSM5CTM1m3LAnR6WsXXIiIiXiA16ShbVi/BVlyE1ceX/iPG0a5Td0+X1Sg0+O4fQLUfMtRDiVIdFbp7nFXaNo7sx/9CZOeOZevKYppjnhuez38tIiLSgDkdDvZsXc/B3VsBCI+KIX7cVELDIz1cmVRXneyoeCEFBQX4qjm5VFFpamqlQG0ChU/8hcjOV3iuMBERkVq0Yek3nD55DICOPfrSe/AorG40fxDPq5f/agcOHCAjI4M2bdrUx+3Ei+StWEn+qlWEjBlDaMJYinbtpnDrVgx//wqBGsoeQgwpyEafd4iISGPRoWsvMtNOMWDUlbSO6+TpcqQGqhyqFyxYwIIFCyqM5eTkcPfdd1/0PaZpkp2dzZo1azAMg1GjRrlfqTQ6x265laIdOwDI/vhjrJGROLKyLnq+aRhla6VFRES8lMNuJy8ni4hmMQC0iutEdMs26j3dCFQ5VO/YsYN33nnHteELQFFREe+8806V3h8TE8Ps2bPdKlIan7wVK12ButylArWIiIi3y83OJHH5QooL8xl//e0EBocAKFA3ElUO1f369ePOO+90vX733XcJDAzkpptuuuh7LBYLYWFh9OrVi5/97GdERETUqFhpPPJXrar2ewzTLOvsoQcRRUTEi5imyfGDe9m5YQUOux3/gCAK83NdoVoahxq11IuNjSUlJaW2a/IaaqnnvrwVKzl5//0Vxipt3nL+a4sFx4dfqVWeiIh4jVKbjR3rl5N0eD8AzVu1Y9CYSQQEBXu4sqajwbfUW7FiBX5+frVZizQhoQljK6yhNgHT1xdKSzHKX/foDfv3YDid2sxFRES8TnZGGokrFpKfm41hGHQfMIyufQdrq/FGyu1QPWbMmNqsQ5qYol27K6yhNgBKS3E88meM/DzMXn2hWw9t5iIiIl7r6IEfyM/NJjA4lPiEKTRr0crTJUkdUiNE8YjCrVsrjRlQFqin3/rToDZzERERL9V7yCisVivd+g/Rw4hNQJVC9bhx4wBo3749c+fOrTBWHYZhsGzZsmq/TxqfoIEDK42ZUDZDLSIi4oXOnE7h2IEfGDDqSgzDwMfHlz5D9cl+U1GlUL1y5UoAunXrVmmsOrSGSMr5NI+58IFm0fVbiIiISA2ZpsmPuzazd+sGTNMkIroFV/TQJFFTU6VQXd5fOjo6utKYiDtsx45XGjNALfNERMSrFBcWsGXVYtJSTgDQ9oqutOvU3cNViSe43VJP1FKvJkpTUzk0bnyFrcjVMk9ERLzJ6eTjbFm5mJLiQqxWH/oOT6B95x76ZL6Bqa+WepY6u7LIJfjGxtLymTmu16ahlnkiIuI9Du3ZzrrvvqSkuJCwyGYkXHsrcV16KlA3YW6H6vXr19dmHdIERUyfDgH+ABT37os55RoPVyQiIlI10S1aY7FYievai4RrbiUsspmnSxIPq9GOildccQV33HEHt99+Ox07dqzt2ho8Lf+omX09e4HDAZzt/GG14ly8zrNFiYiIXERBXg7BoeE/vc7NITgs/BLvkIbAK5Z/HD58mDlz5tC5c2dGjhzJv//9b3JycmqrNmnEkp/4kytQw9mHFB0OePk5zxUlIiJyAQ67nR0bVvD9/PfISj/tGleglnO5HaoPHTrE7NmzueKKKzBNk/Xr13PffffRsmVLbr75Zr755hsc54QmkXPlr1pVacwAjE1aViQiIg1HXk4WK//7CUf27sTpdJCeetLTJUkD5Xao7tixI7Nnz+bHH390BerIyEiKi4v57LPPuO6662jVqhUPPvggW7Zsqc2apREIucA29yZgDhle/8WIiIhcwIlD+1ixYB45Z9LxCwhk+MRr6dK78uZlIlDLLfVKS0tZuHAh7733HgsXLqSkpMT1FGzXrl258847efTRR2vrdh6nNdXus6WkcHjc+ApjJuD46Gt1ABEREY+yl5ayc8MKjh/cC0B0yzYMHjOZwOAQD1cm7vCKNdXn8/X15dprr+Xzzz/n1KlT/N///R/Dhw/HNE3279/PE088UaPrb968malTpxIZGUlwcDDx8fHMmzevWtfIzs7mqaeeok+fPoSGhhIdHc3gwYN57bXXKC4urlF9UlnRrt2cmfsORbt2A2BPTyfjjX9x7KabK51bvvmLiIiIJyUd3l8WqA2D7v2HMmryDQrUcllV2lHRHREREdx9993ExMRQXFzM1q1ba3S9lStXMmnSJPz8/LjlllsIDw/niy++YMaMGRw7dqxKgT07O5uBAwdy5MgRRo4cyS9/+UtKSkpYtGgRv/nNb/jyyy/5/vvvsVjUvrs2pDz2ODlffeV67dOyJfb0dLDbgbKZ6XO7eZoWC2brtvVao4iIyPniuvYiMz2Vdp26E9OyjafLES9RJzsqbtiwgffff59PP/2UrKwsAEzTpHnz5qSmplb7ena7nW7dunHy5Ek2bNhA//79AcjLy2PYsGEcOHCAvXv30rlz50te58UXX+TRRx/loYce4u9//7tr3GazMXLkSDZv3syqVasYPXp0lerS8o+LK9q1m2M33XTBYyVde5E/8WoC7aUE/usVDKcT01K2+Yt6VYuISH2zlRSzf0ciPQYMw8fX19PlSC2rr+UftTZTfeTIET744APef/99jhw5ApQFaX9/f6ZNm8bMmTOZMmWKW9devnw5hw8f5uc//7krUAOEhoby5JNPcssttzB37lz+53/+57I1AkydOrXCuJ+fH1deeSWbN28mLS3NrRqlTGlqKrZjxynYtOmCx/OvvxXrfb8h3Fr2aYBj9BiM5KSyGWqtpRYRkXqWmXaKxBWLKMzPpdRWwsBRV3q6JPFSNQrV2dnZfPrpp7z33nts2LABKAvSACNGjGDmzJncdNNNhIfXrI/jypUrAZg4cWKlY+Vjqy7Qou18PXv2BOC7775jwoQJrvHS0lKWLl1KYGAgw4YNq1GtTVn2/Pmcemo2OJ1wgW1aTSBg/JVgPWd5TUxzTIVpERGpZ6ZpcnD3VvZsWY9pOgkKDaNDt96eLku8mNuhevr06Xz77bfYbDZXkC7fYfGOO+6gQ4cOtVbkwYMHAS64vCMyMpLo6GjXOZcya9Ys3n//ff72t7+xZcsWBg8eTElJCd999x1ZWVnMmzeP1q1bX/T9JSUllJSUuF7n5ua68atpnEpTU38K1AC1v6pIRESkVpQUFbJl9RJOnzwGQOsOnRkwcgK+fv6eLUy8mtuh+osvvgDKQu1NN93EHXfcwfDhddNjuHyXxovNeIeFhXHy5OWbsQcGBrJy5Up++ctf8sEHH7hmty0WC7/+9a8ZOXLkJd///PPPM2fOnGpW3zTYjh3/KVBfhAEYP+zE7NajfooSERE5T2Z6KhuXfkNxYQEWq5W+Q8cS17WXqwWwiLvcbnMxbdo0Pvvsswqt8xq6jIwMrrzySjZu3Mi3335LdnY2qampvPHGG8ydO5chQ4a4Hqy8kMcff5ycnBzXV1KS2r+VpqZSsHETlqAgOK9ryvlz1SZg9upbb7WJiIicLzAoBNPpJDQiioRrbqVDt94K1FIr3J6pXrBgQW3WcUnlM9TlM9bnK+/CcTkPP/ww69evZ+fOnfTp08d17XvuuQeHw8H999/PP/7xj4vORvv7++Pvr4+Gyp2/htqnVSvsycnA2QDdsjWcSsYofz1xKmiWWkRE6lmprcS1tCMwOIQRk68nJCxSnT6kVtVZn+raVL6W+uDBgwwcWHF70KysLDIyMqo0U/7tt98SFRXlCtTnGjduHECN+2k3FRdaQ10eqOFs/+nTp3A8+3JZd49efRWoRUSk3p06cZSta5bQf/g4WncoyxMRzfSAvNQ+r9jlZMyYMQAsWbKk0rHysfJzLsVms5Gbm4vNZqt0LD09HUAz0VVUpTXUTidGYCDm9FsVqEVEpF45HQ52bVrNhu8XYCsu4si+XdTB1hwiLlUK1VarFavV6mpJd+5Ydb58fNybGB8/fjwdO3Zk3rx57NixwzWel5fHs88+i4+PD3fddZdrPCMjg/3795ORkVHhOiNGjMBut/Pss89WGC8pKXGNJSQkuFVjU+MX175S27xKa6i1Q6KIiHhAQW4Oq/77KYd+2AbAFT36MXzStVo7LXWqSqHaNE3X14XGqvPlDh8fH9566y2cTiejRo3i3nvv5ZFHHqFv377s2bOHp59+mi5durjOf+211+jevTuvvfZaheu88MILhIaG8txzzzFkyBAefvhhfvWrX9GjRw8WL17MwIEDmTVrlls1Shnz7Des8h0StaGLiIjUp5NHDrDsqw/JyjiNr58/QydMo++wsVitXrHiVbxYlf6ErVixAoCgoKBKY/UlISGBtWvXMnv2bD799FNsNhs9e/bk2WefZcaMGVW6Rr9+/di6dSvPP/88y5Yt47XXXsPHx4dOnToxZ84cHnnkEQICAur4V9I42I4dr9SL2gAcf34OwiO0Q6KIiNS77DNpJK5YBECzFq0YPHYKQSGhHq5KmgrD1AIjt5V3HanrveQbotLUVA6NG19hXbVpseD48CuFaRER8ZidG1fi4+tH9/5DsVi84tExqWP5ebkM79GuzvOa/rSJW3xjY2n5zBzXumrTMLTcQ0RE6pVpmhz/cQ+FBXmusT5DxtBz4HAFaql3bv+JGzduHDfeeGOVz7/11lsZP368u7eTBihi+nTCpk4FIO+amzCnXOPhikREpKkotZWweeV3bF3zPZtXfIfz7CenehhRPMXtVfsrV64kNja2yudv3LiREydOuHs7aaAsZ9fZm0HBHq5ERESaiqyM0yQuX0hBXg6GYRDbNk5hWjyu3h6FdTqd+gMvIiIibjNNk8N7trN781pMp5PA4FDiE6bQrEUrT5cmUj+h2uFwkJaWRnCwZjNFRESk+mwlxWxZvYTUE0cAaNn+CgaOuhI/f3XtkoahyqE6NzeX7OzsCmMOh4OkpKSL9p82TZPs7Gzmzp1LSUnJBbcHFxEREbkci9VKYW4OFouV3kNG0bF7X30CLg1KlUP1K6+8wjPPPFNhLCMjg7i4uCq93zAM7rjjjmoVJyIiIk2X6XSCYWAYBj4+vsSPm4rT4SAiWp2mpOGp1vKPc2ekDcOo8g6JrVu35r777uPXv/519aqTBqlo124Kt24laOBAbMnJAFiT9RCqiIjUnqLCAras/I7mrdvRte9gAMIim3m4KpGLq/LmLzk5Oa7lH6Zp0rFjR2JiYkhMTLzoeywWC2FhYYSHh9dKsQ1NU9z8JeWxx8n56qtK4yZg9uiN89V/13tNIiLSuJw+eYwtqxZTUlyEr58fk266W2unxW31tflLlWeqw8PDK4Tj0aNHEx0dTfv27eukMGl4inbtvmCghrItytm7GzashWEj67MsERFpJJxOB3u3rOfH3VsBCI+KJj5hqgK1eIUa9amWpqVw69ZLHjcAI3EDpkK1iIhUU0FeDptXLCIzPRWAjt370Dt+NFafeuv+K1Ij+pMqVRY0cOAlj5uAGT+sfooREZFGw24vZeU3n1BSVIivnx8DRl5J6w6dPV2WSLVUKVSvXr0agKCgIAYNGlRhrLpGjx7t1vukYTIpm6EuX1OtpR8iIlJdPj6+dOsbz4nD+4lPmEJwaON8FksatyqF6rFjx2IYBt26dWPPnj0VxqrDMAzsdnv1q5QGoWDrlkpjBuDo0Qfz1pkK1CIiUmV52Zk4HHYimpW1x+vYoy8duvfGYrF6uDIR91R5+Ydpmjidzkpj1VHd86VhMQsKKo8B5q8ehG496r0eERHxTscP7mXH+hUEBAYx7rrb8PXzxzAMDEOBWrxXlUL1+WH6YmPSeNmzssj6cB5w3pKPiVMVqEVEpErspTZ2rF/BiUP7AAgKCcXhcODr4bpEaoMeVJQqSfvb33BkZVHaLo6S3zxK4OH9mL36KlCLiEiVZJ9JI3HFIvJzssAw6N5/KN36DsawWDxdmkitUKiWy8pdvJic+Z8DkP3L3xPZvz9m//4erkpERLyBaZoc2beL3YmrcTocBASFEJ8whejY1p4uTaRW1VmoTk9PZ+3atVitVkaPHk1ERERd3UrqUObHH3P66TlA2XKPiIwUzxYkIiJeJzXpKE6Hg9i2HRg4eiL+AYGeLkmk1rn9mcuWLVu4++67+dvf/lbp2Mcff0xcXBzTp0/n+uuvp127dnz55Zc1KlTqX2lqKqfnPON6bQA+//wrpKd5rigREfEK5c0JDMNg0OiJ9BuewLArr1GglkbL7VA9b9483n33XSznrYVKSUnhF7/4BUVFRZimiWma5Ofnc9ttt3H48OEaFyz1x3bsOJzXscVwOjGSkzxUkYiINHSmaXJg52a2r1vmGvMPDKJj977VbsUr4k3cDtXlm79cc801FcbffPNNioqK6NOnDwcPHiQpKYkxY8Zgs9l49dVXa1at1Cu/uPZw3jdA02LBbN3WQxWJiEhDVlxUwLrFX7JnyzqOHfiBjFMnPV2SSL1xO1SfOnUKwzBo3759hfFvv/0WwzB47rnnuOKKK2jdujX//Oc/MU2T5cuX17hgqT++sbGETJjgem1aLDgfegximnuwKhERaYjSUk6w7MsPSUs+gdXqQ/+RE2imhxGlCXH7QcUzZ84QERGBj89PlygqKmLHjh34+/szceJE13ifPn3w8/Pj2LFjNSpW6l9g797kf/89Rf3j8f3jnxWoRUSkAqfTyb5tGzmwMxGAsIhmxI+bSlhkMw9XJlK/3A7VPj4+5ObmVhjbvHkzDoeDYcOG4efnV+FYSEgIBRfYkU+8gyOyGb4K1CIicp7EFQtJOXYIgLiuvegzdAw+PtrORZoet5d/xMXF4XA42Lx5s2vs66+/xjAMRowYUeFch8NBTk4OzZsrlImIiDQmcV174evnR3zCFAaMnKBALU2W26H6yiuvxDRNHnjgATZt2sRXX33Fm2++CcC0adMqnLt7924cDgdt2rSpWbXiMdasM2qlJyIiOBx2sjN++vsgtk0ck266mzYdu3qwKhHPcztUP/LII0RERLB161aGDx/Oz372M/Lz80lISGD48OEVzi1/eHHYsGE1LljqV9Hu3QAEbk/EOuM6jEVfe7giERHxlPzcbFZ98ylrFs2nIC/HNe7nH+DBqkQaBrdDdevWrVmxYgUJCQkEBAQQGxvLPffcw+eff17hPNM0mTt3LqZpkpCQUOOCpf4U7f6B/O+/d702nE4sr7ygGWsRkSYo6fB+ln81j+wzaRiGhcL8PE+XJNKg1Gib8r59+7J06dJLnuN0Olm2rKwBfOvWaq3TEJSmpmI7dhy/uPb4xsZWeO0TE0PBunVkffop+ctXVHpv+eYvph5aFBFpEuz2UnZuWMnxH/cAEB3bmkFjJxMUHOrhykQalhqF6qqwWq2VelmL52TPn8+pp2aD0wkWC+HXXEPO11+XvTYMrGFhOHJ++kjPpGx7ctdrbf4iItJk5GRmkLhiIXnZmQB06z+Ebv2GVNpNWUTqIVRLw1GamvpToAZwOsn56qufTjBNHDk5OIOCyU+YTOnkawk7sg+ff/4Vw+nU5i8iIk3M8R/3kJediX9gEIPHTqF5K02qiFxMrYTqlJQUdu/eTWZmJqWlpZc8d+bMmbVxS3FD3spVPwXqSyh87BkChw0nyDCgexcc8cPKlny0bqtALSLShPQcPAITk6594wkIDPJ0OSINWo1C9e7du/nNb37DmjVrqnS+YRgK1R5QmppK5ocfkjn3nUrHLrS8I6BzZzDOGY1prjXUIiJNQGZ6Kkf27mTAqCuxWCxYrT70HTrW02WJeAW3Q/WBAwcYNWoUeXl5mKaJn58fMTExFbYtF8/Lnj+fU08+BaYJgD0qGmt2pms5hzlhMiz9Tss7RESaMNM0OfTDNn7YvA7TdBIWFU2X3gM9XZaIV3E7AT/99NPk5ubSqlUr3njjDaZMmYLVaq3N2qSGSlNTKwRqAGt2Jo5X38IoLvppOcfP79PyDhGRJqqkuIgtqxZz+uQxAFrHdSauS0/PFiXihdwO1StWrMAwDN577z3GjRtXmzVJLbEdO14hUMPZlnjFRZj9zpmB0PIOEZEmKf3USTavXERxYQEWq5U+Q8bQoVtvjHOXAIpIlbgdqnNycvD392fs2LG1WI7UJr+4yq0MTcNQSzwREeHo/t1sX78cTJOQ8EjiE6YS0SzG02WJeC23Q3XLli1JT09Xr8qGzjAqzVaLiIg0a9EKq8VK645d6DcsAR9fX0+XJOLV3E7E06ZNo7CwkO3bt9dmPVKLLrj8wzQxkpM8VJGIiHhSQd5Pm3uFRTZjwg13MGj0RAVqkVrgdqj+05/+RHR0NA8++CAlJSW1WZPUEi3/EBERAKfDwe5Nq1ny2bucOZ3iGg8OC/dgVSKNi9vLP4qLi5k7dy533HEHAwYM4JFHHiE+Pp7Q0NBLvq9du3bu3lKqydSyDxGRJq8gL4fEFQvJSj8NQFpKEs1atPJwVSKNj9uhukOHDq6fZ2dnM2vWrMu+xzAM7Ha7u7eUs0pTU7EdO45fXHt8Y2MveLx4/wEyXn+90rHy5R/q9iEi0vglHz3ItrXfU2qz4evnz4BRV9I6rpOnyxJplNwO1e7MgmrmtOay58/n1FOzy7Ybt1ho/sgjhF11let47rffkvbSS6611BfaMVHLP0REGjeH3c6uTas4un83AFHNWxI/dgpBoWEerkyk8XI7VB89erQ265AqKE1N/SlQAzidpL34ImkvvnjxNxlGWbA2Te2YKCLSRCQfPegK1F36DqbHgKFYLNqgTaQuuR2q27ev/BCc1C3bseM/BepzmIbhap1nXKDbh+PJv0B4hHZMFBFpItp26saZtBRaxXWiRWv9fS1SH9wO1VL//OLag8VSIVibFgvF731RFpbT0wiYeQPGecfNHr0VpkVEGrFSm4392zfSrf8QfP38MQyD/iPGe7oskSal1nZuSU9PZ8uWLaxevbq2Linn8Y2NJXb2bNfr8uUcvrGx+Fot+MbG4nzoMcyzG/JouYeISOOXnZHGigXzOPjDNnasX+HpckSarBrPVH/99dc8/fTT7Ny5E6jc4SMrK4tbb70VgM8//5zg4OCa3rJJi/jZDaSeDdaFr7+Df+cuFY6bU67BMWhoWYcPLfcQEWm0TNPkyN6d7E5cg9PpIDA4lA7denu6LJEmq0ah+oUXXuBPf/rTJbt6REZGEhQUxIIFC1i4cCE33nhjTW4p5zCbxVz4QExztcwTEWnEbCXFbF29hFMnjgDQsl1HBo6eiJ9/gIcrE2m63F7+sWnTJv70pz/h4+PDK6+8QkZGBi1atLjgubfffjumafL111+7XaiIiIhA9pl0ln35IadOHMFisdJn6BiGTpimQC3iYW7PVP/zn/8E4PHHH+d3v/vdJc8dM2YMAJs3b3b3diIiIgIEBgVjmk6CwyKIT5hKZLQ+mRRpCNwO1WvXrgXg17/+9WXPbdasGSEhISQnJ7t7OxERkSar1FaCr58/AP6BQYyYdB1BIeH4+vl5uDIRKef28o+0tDRCQ0OJjo6u0vm+vr7YbDZ3byciItIknU4+zpL573Li0D7XWHhUjAK1SAPjdqgOCgqisLAQ5wU2Izlfbm4u2dnZREZGuns7ERGRJsXpdPLDlnWs++5LSooKObJv1yUbA4iIZ7kdqrt06YLD4WDXrl2XPffzzz/HNE369u3r7u3kAowz6Z4uQURE6kBhfi6rv/2MH3eWPYvUoVtvRk35GYZheLgyEbkYt0P1tGnTME2TF1544ZLnHTp0iMceewzDMLjuuuvcvZ2clf35F66fB/3qToxF6qgiItKYpBw7xLIvPyQz7RQ+vn7Ej5tK/xHjsfpoE2SRhsztUP2b3/yG5s2b89lnn/Hzn/+c/fv3Vzh+5MgR/ud//ofBgweTnp5OXFwcd999d40LbspKU1NJnTPH9dowTSyvvADpaR6sSkREaktediYbl/2XUlsJkTEtGH/9DNp06HL5N4qIx7n9z96wsDAWLFjA5MmTee+993jvvfdcx0JCQigqKgLKdnxq1qwZX3zxBf7+/jWvuAmzHTsO561hN5zOst0TtdmLiIjXC42IokufQZimSc+Bw7FYrZ4uSUSqyO2ZaoAhQ4awY8cObrjhBgzDwDRNTNOksLDQ9TDFddddR2JiotZT1wLfVq0qjZkWS9l25CIi4pVOHNpPQV6O63XPQSPoHT9KgVrEy9R4gVb79u357LPPyMrKYsOGDaSkpOBwOIiNjWX48OHExFxkK22ptqKzD4WagEFZoHY+9BhollpExOvYS23s2LCCEwf3ERnTgjFX3YTFatXDiCJeqtaeeoiMjGTq1Km1dTm5gKx58wDIvXo6IWMTymaoFahFRLxOTmY6m5YvJD8nCwyD2DYdFKZFvJweJfYSxfv3U7RtG6bVimP6DMw2LT1dkoiIVJNpmhzdv4tdm1bjdDgICApm8NgpxLRs4+nSRKSGaj1U7969m7lz53LgwAH8/f0ZMGAAs2bNIjY2trZv1aRkzfsIgML4kQS30u+liIi3KbXZ2LpmCSnHDgHQok0cg0ZPxD8wyMOViUhtqHKoPnnyJE899RRWq5XXXnvtgp083nrrLX71q1/hcDhcYwsWLODvf/87//3vfxk+fHjtVN3EFB88SPZXXwFQNPV6Iiz6iFBExNtYrBYK8nIwLBZ6DRpJp179teRDpBGpcvePZcuW8c4775CSknLBQL1r1y5XoDZNk4CAACIiIjBNk+zsbKZPn05+fn6tFt8UZM+fz9FrrgWbDRMIPZPq6ZJERKSKTNPEPNsK1Wr1YUjCVMZcfROdew9QoBZpZKocqlevXo1hGNx4440XPP78889jt9vx8fHhP//5D3l5eZw5c4YFCxYQFBTE6dOneffdd2ut8KagNDWVU0/NhrPtCQ3A79UXtdmLiIgXKCkqZP2SBezbsck1FhIeSVSMlvCJNEZVDtW7zrZzS0hIqHTMZrPx9ddfYxgGDzzwAHfddRcWS9mlp02bxh/+8AdM0+Tbb7+tpbKbhktt9iIiIg1XekoSy776kNMnj3Fw9zaKiwo9XZKI1LEqh+rTp0/j7+9P+/btKx3bunWrawfFO++8s9Lxn//85wDs2bPH3TqbJMOncuN/bfYiItJwOZ1O9m7bwJpFn1NcWEBoRBRjp91MgB5GFGn0qvygYlpaGiEhIRc8tnnzZgBCQ0MvuHNi27Zt8fX1JSMjw80ymx7TNMn4f/9X9nO02YuISENXWJDHlpXfkZGaDED7Lj3pO3QsPr6+Hq5MROpDlUO1n58f2dnZrnXT59q6dSvARbciNwyD0NBQcnNza1Bq01GamkrWRx9TsH49pq8fWXNeJtzPqs1eREQaKIfDzqpvPqWoIA8fX1/6jxhP2yu6ebosEalHVQ7Vbdq04cCBA2zbto34+PgKx8ofYjx/vJzT6SQnJ4eIiIgaFdsUZM+fX/Zw4tm11IX94wkZPBhTT4mLiDRYVqsP3fsP4ci+XcSPm0pIWISnSxKRelblNdUjRozANE3++te/VhhfunQpx48fB2DChAkXfO+ePXtwOBx06NChBqU2fq5uH+c8nBi0ZT2WjHQPViUiIheSn5tNVsZp1+v2XXoy9pqbFahFmqgqh+p77rkHgK+++oqrr76af/3rXzz55JNMnz4dwzBo06bNRUP10qVLAejfv38tlNx4qduHiIh3OHnkAMu/msfGpf/FVlIMlC11tFgqP2AuIk1DlZd/xMfH89vf/pZXX32VRYsWsWjRIqDsgTrDMHj55ZexWi/8zeSDDz7AMAxGjx5dO1U3Un5x7cFiqRCs1e1DRKThsNtL2bVxFccO/ABAeFQ0DrsdKu+JJiJNTJVnqgH+8Y9/8PLLL9OqVauyXaJMkw4dOvDBBx9cdFOYlStXsn37dqxWK1OnTq1RsZs3b2bq1KlERkYSHBxMfHw88+bNq/Z18vLymD17Nr169SIoKIiIiAgGDBjAnDlzalRfTfnGxtLymZ9qMA11+xARaShys86wcsHHrkDdtW88o6ZOJzD4wp2xRKRpMUzz7HZ91VTeHi86OvqS55WWlmKz2bBYLAQGBrpzK6AsnE+aNAk/Pz9uueUWwsPD+eKLLzh69Ch/+ctfeOKJJ6p0nRMnTjBu3DiOHDnChAkT6N+/PyUlJRw6dIgTJ064NrmpitzcXMLDw8nJySEsLMzdX1olP44ajSM9nbynXyRwpGb3RUQ8yTRNjv24h10bVuJw2PEPDGLwmMk0b93O06WJSBXk5+UyvEe7Ws9r56vy8o/zXS5Ml/P19cW3hj067XY7s2bNwjAMVq9e7VqbPXv2bIYNG8bs2bO58cYb6dy58yWv43A4mD59OikpKSxbtqzS7pB2u71GdYqISON0OukoDoed5q3bMWjMJAICgz1dkog0MNVa/uEpy5cv5/Dhw9x2220VHnYMDQ3lySefxG63M3fu3MteZ/78+WzevJlHHnnkgtutn99/2xOy58/HkV7W7SNkzqMYi772cEUiIk1T+Qe5hmEwYNSV9Bk6hhGTrlegFpELqlKKLCoqqtHSjYspLCwkKOjyW7euXLkSgIkTJ1Y6Vj62atWqy17nk08+AeDGG28kKSmJb7/9luzsbK644gqmTJly0R0j64urpd5ZhmlieeUFHIOGal21iEg9MU2Tw3u2k30mnYGjJ2IYBn7+AXTqqQ5WInJxVZqpjouL4+9//zvFxcW1ctMtW7Zw9dVX87e//a1K5x88eBDggss7IiMjiY6Odp1zufsCrF27ls6dO3P//ffz+OOPc9NNN9GxY0dXeL+YkpIScnNzK3zVJrXUExHxrJLiIjYs/YZdm1Zz4tA+0pKPe7okEfESVQrVJSUl/OEPfyAuLo7HHnuM3bt3V/tG+fn5vPfee0yYMIEhQ4awcOHCKu+wmJOTA0B4ePgFj4eFhbnOuZS0tDQAfvOb3/Dggw+SlJREeno6r776Kjk5OVx33XWcOnXqou9//vnnCQ8Pd321bVu7re5cLfXOoZZ6IiL1IyM1meVffUjqiSNYrFb6Dkugeev2ni5LRLxElbp/ZGZmMnv2bP71r3/hcDgA6N69O6NHjyY+Pp6+ffsSExNDVFQU/v7+ZGVlkZmZyZEjR0hMTGTTpk2sWrWKoqIiTNOkR48evPjii1VusTdx4kS+//57Dh48SKdOnSodv+KKKzh58iQlJSWXvI6fnx+lpaVce+21fPXVVxWOPfbYY/z1r3/l2Wef5c9//vMF319SUlLhHrm5ubRt27ZWnybNnj+fU39+EjjbUu/hxzCnXFMr1xYRkcpMp5MDOzezd/tGME1CwiOJT5hCRDMtuxNpDBpU94+oqCj+93//l9/+9rf87W9/46OPPmLv3r3s27ePf/3rX5d9f3luj4+P54EHHmDGjBlYLFV/RrJ8hvpis9Hlre2qcp2MjAyuuaZySJ02bRp//etfXUtELsTf3x9//7rt8B8xfTpp/3wVR3o6+bNfUEs9EZE6tmX1EpIO7wegXafu9BuegI+vn4erEhFvU63uH507d+aNN94gJSWFN998k+uvv56YmBjXRjDnf1mtVgYPHswf//hHtm/fzsaNG7njjjuqFajL7wtccN10VlYWGRkZl22nB9C1a1eACy47KR8rKiqqVm11wTi7M6UZEeXhSkREGr+4rj3x8fVj4OiJDBozSYFaRNziVg+54OBgZs2axaxZswA4evQoKSkppKenU1xcTLNmzYiJiaFLly5V6u5xOWPGjOH5559nyZIl3HLLLRWOLVmyxHXO5YwbN45169axd+9ebrjhhgrH9u7dC5Q9lCkiIo2X0+kgJzODyOgWAMS0bMvkm+/Gzz/Aw5WJiDdze0fF+mS32+natSvJycls3LiRfv36AWXbjQ8bNowDBw6wZ88eunTpApTt9piRkUF0dHSFTWqOHj1K9+7dCQ8PZ9u2bbRu3dp1ndGjR7Njxw6WLl3K+PHjq1RXXe2oeHBsAvbUVHL/8RZBvXrV2nVFRJq6grwcElcsIjfrDOOuu43Q8EhPlyQiday+1lR7xeYvPj4+vPXWWzidTkaNGsW9997LI488Qt++fdmzZw9PP/20K1ADvPbaa3Tv3p3XXnutwnU6dOjASy+9RFpaGn379uWee+7h17/+NX369GHHjh3ce++9VQ7UIiLiXZKPHmT5Vx+SlZ6KxWJQmFe7bVFFpGnz/BaCVZSQkMDatWuZPXs2n376KTabjZ49e/Lss88yY8aMKl/nN7/5DXFxcbz00kt8/PHH2O12evbsyRNPPME999xTh78CERHxBIfdzu7E1RzZtwuAyJhY4hOmEBx6+QfcRUSqyiuWfzRUdbX848dRo3Gkp5P39Ivq/iEiUgN52ZkkrlhITmYGAF16D6THoOFYLFYPVyYi9UXLP5qo7PnzcaSnAxAy51GMRV97uCIREe914tA+cjIz8A8IZPik6+gVP0qBWkTqhNcs/2gKSlNTOfXUbNdrwzSxvPICjkFDIUabEIiIVFf3AUNx2O107j2QwOAQT5cjIo2YZqobENux4+B0VhgznE6M5CQPVSQi4l2yz6SzeeV3OJ1lu/9aLFb6DB2jQC0idU4z1Q2IX1x7MAw4Z5m7abFgtm7rwapERBo+0zQ5sm8XuxNX43Q4CAmPpHv/IZ4uS0SaEIXqBsQaHo7h749ZXAyUBWrnQ49p6YeIyCXYSorZtnYpKccOARDbriMdu/fxcFUi0tQoVDcguQsXYhYXY49uTunDf8K3QwcFahGRSzhzOoXNKxdRmJ+HYbHQe/AorujZD8MwPF2aiDQxtRaqTdPkzJkzFBYW0q5du9q6bJNhmiZZH84DIG/ydYTG62NLEZFLOXFwH1vXLME0TYJDw4kfN9W19biISH2r8YOK27Zt44YbbiA8PJwWLVrQsWPHCsezsrL45S9/yX333YfNZqvp7Rqt4p07Kd67F9PXDyZP83Q5IiINXlTzWKw+PrTp2JVx192mQC0iHlWjmer333+fWbNmUVpaetFzIiMjOXr0KMuWLWPatGlcddVVNbllo5X10UcAFIxIILhFtIerERFpmArzcgkKLdu8ISQ8kvHX3U5QaJiWe4iIx7k9U71v3z7uueceSktL+e1vf8uWLVuIjr5wGJw5cyamabJgwQK3C23MivbvJ+e/3wJQfNX1WPSXg4hIBU6nkz1b1rP4s3dIS/mpzWhwWLgCtYg0CG7PVP/973/HZrPxwAMP8I9//AMAq/XCu1SNGzcOgA0bNrh7u0Yre/58Tj35FJgmJhCWchz69/N0WSIiDUZhfh6bVy7izOkUANJSTtC8lVqNikjD4naoXr58OYZh8Oijj1723FatWhEUFMSJEyfcvV2j5NpB8WxfagPw/edfccQPU9cPEREg5fhhtq35HltJMT6+fgwYOZ42Hbt6uiwRkUrcDtUpKSkEBwfTpk2bKp0fGBhITk6Ou7drlC61g6KpUC0iTZjDYeeHzWs5vGcHABHRLYhPmEJIWIRH6xIRuRi3Q7W/vz/FxcWYpnnZ9WxFRUVkZ2cTERHh7u0aJe2gKCJyYaknjroCdaee/ek1eCSWiywxFBFpCNx+UDEuLo7S0lIOHjx42XMXLlyIw+GgR48e7t6uUfKNjcWnZUvXa+2gKCJSplVcJzp278uwK6+hz9AxCtQi0uC5HaonT56MaZr885//vOR5Z86c4Y9//COGYaid3nlKT53CnpKCCeQ9/hyOD7/CnHKNp8sSEal39tJSdieuwVZSDIBhGPQbnkDLdh0v804RkYbB7VD90EMPERISwhtvvMGcOXPIy8urcLyoqIh58+YxaNAgjh49SrNmzbjvvvtqXHBjkrd8OQC2br3wSxivGWoRaZJyMjNY8fVHHNy9lW1rl3q6HBERt7gdqlu0aMG8efPw9fXlmWeeISYmhjNnzgDQs2dPoqKiuOOOOzh+/Dj+/v589NFHhIWF1VrhjUH+smUAFA4eidWiPqsi0rSYpsnR/btZ8fVH5GVnEhAUzBXd+3q6LBERt9Rom/Krr76a1atXM3DgQGw2G3a7HdM02bdvHyUlJZimSf/+/Vm9ejXjx4+vrZobBUdODgWJmwEwR4zycDUiIvWr1FZC4oqFbF+3DKfDQYs27Rl33Qxi1H9aRLxUjbYpB4iPjycxMZFdu3axdu1aUlJScDgcxMbGMmLECAYNGlQbdTY6+atXg91Oads4Ajt08HQ5IiL1Jjc7kw1LFlCQl4NhWOg5eASdew3Qzogi4tVqHKrL9enThz59+tTW5Rq9vO/L1g0Wxo8k2FqjDwxERLxKQGAQTqeToJAw4hOmENW85eXfJCLSwLkdqt977z0CAwO58cYbq3T+F198QX5+PjNnznT3lo2Gs7iY/LVrAHAMG+3hakRE6l6prQQfXz8Mw8DPP4DhE68lMDgEP/8AT5cmIlIrDNM8Z+eRarBYLLRs2ZLk5OQqnd+hQweSkpKw2+3u3K5Bys3NJTw8nJycnGo9hJm3YgUn7/8VjmbRFH/wFf6+tfaBgYhIg5N+6iSbVy6ie/+hdOjW29PliEgTk5+Xy/Ae7aqd16qrRusOqpvH3czvjU7eOV0/FKhFpLEynU72bdvImkWfU1xYwJH9uzCdTk+XJSJSJ+ot0eXm5uLn51dft2uwTIeD/OUrACgdNppAD9cjIlIXigry2bzqOzJOnQSgXece9BuWgGHRMyQi0jjVS6jesGEDWVlZdFCXC4p27MCRmYkzOATf/gM9XY6ISK1LTTrKltVLsBUXYfXxpf+IcbTr1N3TZYmI1Kkqh+p3332Xd999t8JYZmYm48aNu+h7TNMkOzubPXv2YBgGEyZMcL/SRiJvadnSj6KBQwkI1My9iDQuBXk5bPj+a0zTJDwqhvhxUwkNj/R0WSIida7KofrYsWOsXLmywpjNZqs0djFdu3bl6aefrkZpjY9pmq711MVDRuGvnqwi0sgEh4bTrd8QSkqK6D14FFYfPTciIk1Dlb/bjR07tsLrOXPmEBISwu9///uLvsdisRAWFkavXr0YO3YsVqvV7UIbg5KDByk9cQLT1w/rkGGeLkdEpFYkHz1IWFS0a0a6W/8h2shFRJqcGrXUi42NJSUlpbZr8hrVbamX8X//R/o/X6Vo4FCsL7yCRX/piIgXc9jt7Nq0iqP7dxMeFcPYaTdrZlpEGpz6aqnn9ne/o0ePNvmZ5+pyraceMpIwBWoR8WK52ZkkLl9IblYGAC3axmFY9H1NRJout0N1+/bta7OORq/01CmK9+zBNAwM7aIoIl7KNE2OH9zLzg0rcNjt+AcEMWjsJFq01t8JItK06XO6epK3bDkAtm69CGoR4+FqRESqz24vZfvaZSQd3g9A81btGDRmEgFBwR6uTETE82ocqnfu3Mnrr7/O2rVrOXnyJAUFBRc91zCMRrVNeXXkLV0KlO2iGKqPSEXEC1ksFgpyszEMgx4Dh9Glz2A9kCgiclaNQvVrr73Gww8/jMPh0Bbkl1D8448UJiYCYI7Q0g8R8R6maWKaJhaLBYvFyuCEKRQXFtCsRStPlyYi0qC4vV/spk2b+N3vfofD4eBXv/oVCxcuBCAqKoqlS5fywQcfcNddd+Hn50d0dDTz5s1j+fLltVa4t8ieP5+j114HTicmELJ/l6dLEhGpEltJMRuXfsOeLetcY8Gh4QrUIiIX4HZLvRkzZvDRRx/x4IMP8ve//x24cJu9HTt2MGnSJMLCwti2bRuhoaG1U3kDcLmWeqWpqRwaNx6cTteYabHg+PAriGlej5WKiFTPmdMpJK5YRFFBHharlYk33kVQcOP5/i0iTUd9tdRze6Z63bp1GIbB7373uwrj52f0fv368b//+78cPnyYl156yd3beSXbseMVAjWA4XRiJCd5qCIRkUszTZP9OxJZ/e1nFBXkERwWwZirb1agFhG5DLdD9enTp/H396/QWs9isVBcXFzp3Ouvvx5fX1+++OILd2/nlfzi2oOl4m+xabFgtm7roYpERC6uuLCAdd99yd6t6zFNk7ZXdGXctbcRGa1P1kRELsftUB0UFISvr2+FsdDQUHJzcykpKakw7uvrS1BQEMePH3f3dl7JNzaWyBm3uV6bFgvOhx7T0g8RaXCcTiervv2MtJQTWH18GDDqSgaNmYyvn5+nSxMR8Qpuh+rWrVuTn59Pbm6ua+yKK64AYPPmzRXOTUlJIScnp0l2CLGGlq3dKeo7GMeHX2FOucbDFYmIVGaxWOgxYChhkc1IuPY24rr0VLs8EZFqcDtU9+nTB4ADBw64xsaOHYtpmjzzzDOuZSA2m43f/va3APTu3bsmtXqloh92A1A8eLhmqEWkQSnMyyUz7ZTrddsrujHuutsIi4jyYFUiIt7J7VB99dVXY5omn3zyiWvsgQcewN/fn2XLltGmTRtGjBhB69at+fLLLzEMg1//+te1UrS3ME2T4l1loZruPTxbjIjIOVKOHWLZVx+yYek3FBcVusYtFqsHqxIR8V5uh+qpU6cye/ZsOnfu7Brr0KED8+bNIzQ0lMzMTDZs2MCZM2cwDIM//vGPzJgxo1aK9halyck4srMxfXywdup8+TeIiNQxh93Ojg0r2Ljsv5TaSggKCcXpaJo73YqI1Ca3d1QMCwtj9uzZlcavv/56xowZw8KFC0lKSiI8PJyJEyfSqVOnGhXqjYp3l81Sl7a/Av/AQA9XIyJNXV5OFonLF5KTmQ5A594D6TlwOBarZqdFRGqqRtuUX0xUVBS33357XVzaqxSdXfpR0rkbgRY98CMinnPi0D52rF+OvbQUv4BABo2eSGzbDp4uS0Sk0XB7+Ud1ZWRk8Mgjj9TX7RqE8plqe6duHq5ERJq60yePYS8tJbplG8ZfN0OBWkSkltV5qM7KyuKJJ56gY8eOvPLKK3V9uwbDdDgo2rsHAKNbTw9XIyJN0bltTPsNH0efIaMZNfkGAoNDPFiViEjj5Nbyj0OHDrFnzx4cDgcdO3akX79+lc7Jz8/n5Zdf5h//+Ad5eXmYpom/v39N6/UaJYcPYxYW4QwIxCcuztPliEgTYpomR/fvJiP1JIPHTsEwDHz9/OnUa4CnSxMRabSqFaqTkpK4/fbbWbt2bYXxfv368eGHH9KtW9kyh/fee48//OEPZGRkYJomQUFB3HPPPU1q+Ufx7h8AsF3RBX9/38ucLSJSO2wlxWxfu4zkYwcBaN2hC63jmt6D4iIi9a3KobqwsJCEhASOHj1aaWfE7du3M2HCBPbv38/jjz/O//t//w/TNAkPD+eBBx7gwQcfJDo6utaLb8jKN32xXdGNIO1KJiL1IDPtFIkrFlGYn4thsdBr0Ehatb/C02WJiDQJVQ7V//rXvzhy5AiGYXD33XczefJkTNPku+++Y+7cuZw6dYrp06ezZMkSAgMD+cMf/sDDDz9MWFhYXdbfYJVv+mLv0t3DlYhIY2eaJgd3b2XPlvWYppOg0DDiE6YSFRPr6dJERJqMKofqr7/+GsMw+NOf/sQzzzzjGr/xxhtp1aoVf/nLX/j+++9p27YtS5YsoWvXrnVSsDdw2mwUn92+3dJNOymKSN3avm4Zxw6ULTlr3aEzA0ZOwNev6TzDIiLSEFS5+8fevXsB+O1vf1vp2O9+9zvXz1988cUmHagBCtatA7sdR2gYfq1be7ocEWnk2nfugY+vH/1HjCc+YaoCtYiIB1Q5VGdlZREaGnrBtdHR0dGEhoYCMH78+Nqrzgtlz5/PyV89AIAlLxe/7//r4YpEpLFxOp1kZZx2vW7WohWTb76bDt16Y+gZDhERj6hyqLbb7QQFBV30ePmxpvZA4rlKU1M59dRsOPsgpwFY//FXSE/zbGEi0mgUFuSxdtHnrP7vZ+RkZrjG/fwDPFiViIjU246KTYHt2HFwOiuMGU4nRnKShyoSkcbk1IkjLP/yQzJSkzEsBoX5uZ4uSUREzqpWn2qHw0FSUlKllnrlx4CLHi/Xrl27apboPfzi2oPFUiFYmxYLZuu2HqxKRLyd0+Hgh81rObRnOwARzZoTP24qIWERni1MRERcqhWqMzIyiLvM7oCXOm4YBna7vTq39Cq+sbG0fGYOp558CkwT0zBwPvQYxDT3dGki4qXyc7NJXLGQ7IyyZWRX9OxHr8EjsVrd2hBXRETqSLW+K19qBlrKREyfTv6ateQtXkzeDTMImnKNp0sSES928vABsjPS8PXzZ+DoidrMRUSkgapyqJ47d25d1tGoWAIDATCDQzxciYh4u659B2MrKaZTrwEEhYR6uhwREbmIKofqO++8sy7rEBERIDfrDPt3JDJw1JVYfXwwLBb6DB3j6bJEROQytChPRKQBME2TYz/uYdeGlTgcdoJCw+g1aISnyxIRkSpSqBYR8bBSWwnb1y3j5JEfAWjeuh2devbzbFEiIlItCtUiIh6UlXGaxOULKcjLwTAMegwcTpc+g7QzooiIl1GoFhHxkJNHf2Tzyu8wnU4Cg0OJT5hCsxatPF2WiIi4QaFaRMRDIqNb4OPjS0zLNgwYdaW2GhcR8WIK1SIi9agwL5eg0DAAgkPDGXftbQSFhmm5h4iIl7N4ugARkabAdDrZt30Tiz97h9Sko67x4LBwBWoRkUZAM9UiInWsqLCALSu/I/1UEgBpySeIbdvBw1WJiEhtUqgWEalDqSePsXXVYkqKi7D6+NJveALtO/fwdFkiIlLLFKpFROqA0+lg75b1/Lh7KwDhUdHEJ0wlNCLKw5WJiEhdqJVQ/fXXX7N48WKOHz9OUVERy5Ytcx0rKChg586dGIbBsGHDauN2IiIN3umTJ1yBumP3PvSOH43VR/MYIiKNVY2+wyclJXHDDTewbds2oGyb3fMfuPH39+fWW2/l5MmT7Nixg969e9fkliIiXqFluw506tmfZi1a0bpDZ0+XIyIidczt7h+FhYVMnDiRrVu30rp1ax544AGCg4Mrnefj48OsWbMwTZMFCxbUqFgRkYbKYbfzw+a1FBcVusb6DB2jQC0i0kS4Hapff/11Dhw4wIABA9i3bx+vvvoqISEhFzz32muvBWDJkiXu3k5EpMHKy85k5Tcf8+OuLWxdvQTTND1dkoiI1DO3Q/X8+fMxDIO///3vF5yhPlevXr3w8fHhxx9/dPd2AGzevJmpU6cSGRlJcHAw8fHxzJs3z+3rlZaW0q9fPwzDoFu3bjWqTUSapuMH97J8wUfkZGbgHxBIp5791HdaRKQJcntN9YEDB7BarYwYMeKy51osFsLDw8nKynL3dqxcuZJJkybh5+fHLbfcQnh4OF988QUzZszg2LFjPPHEE9W+5rPPPsuhQ4fcrklEmi57qY0d61dw4tA+AGJatmXQ2MkEBl16kkFERBont2eqS0pKCAwMxGq1Vun8goIC/P393bqX3W5n1qxZGIbB6tWr+fe//83LL7/Mzp076dmzJ7Nnz+bgwYPVuua2bdt4/vnnef75592qSUSarvzcbJYv+KgsUBsGPQYMY+Tk6xWoRUSaMLdDdfPmzcnPzyc7O/uy5+7cuZPi4mLatGnj1r2WL1/O4cOHue222+jfv79rPDQ0lCeffBK73c7cuXOrfD2bzcZdd93F0KFD+fWvf+1WTSLSdPkHBGGaJoHBIYyeOp1u/YdgWNz+dioiIo2A238LDB8+HIBPP/30suf+5S9/wTAMxowZ49a9Vq5cCcDEiRMrHSsfW7VqVZWv9/TTT3Pw4EHefvttrX0UkSoptZW4HkD09fNj+JXXMO66GUTHtvZwZSIi0hC4Harvu+8+TNPk6aefZu/evRc8p7CwkAceeID58+e73uOO8qUdnTtXbk0VGRlJdHR0lZd/bN68mRdffJE5c+bQpUuXatVRUlJCbm5uhS8RafzOnE5h6RcfcGTvTtdYaEQU/gGBHqxKREQaErdD9ZgxY/jFL35BamoqQ4YM4ZZbbqGgoACAl156iZkzZ9K2bVveeOMNAB588EH69u3r1r1ycnIACA8Pv+DxsLAw1zmXUlJSwl133UX//v35/e9/X+06nn/+ecLDw11fbdu2rfY1RMR7mKbJgZ2bWf3tZxQV5HFk/y6cToenyxIRkQaoRjsqvvHGGwQHB/O///u/rmUghmHw2GOPAT/tsPjwww/z0ksv1bzaGnryySc5ePAgW7durfIDlud6/PHHefjhh12vc3NzFaxFGqniogK2rFpMWvIJANp07EL/EeOxWKr/vUNERBq/GoVqq9XKP/7xD+655x7eeust1q1bR0pKCg6Hg9jYWEaMGME999zj9gx1ufIZ6ovNRufm5l50Frvctm3b+Pvf/86TTz7p9lbp/v7+bncwERHvkZZ8gs2rvqOkqBCr1Yc+w8YS16WnnsEQEZGLqlGoLtezZ09eeeWV2rjUBZWvpT548CADBw6scCwrK4uMjAzXg5MXs2vXLhwOB08//TRPP/10peMHDhzAMAzCw8Or1NFERBqnooJ81i9ZgNPpICyiGfHjphIW2czTZYmISANXK6G6ro0ZM4bnn3+eJUuWcMstt1Q4Vr71+eU6i3Tp0oVf/OIXFzz29ttvEx4ezvTp0wkKCqqdokXEKwUGh9B9wFAK8nLoM3QMPj6+ni5JRES8gGGW94iqpokTJzJz5kxuuOGGOg+idrudrl27kpyczMaNG+nXrx8AeXl5DBs2jAMHDrBnzx5XN4+MjAwyMjKIjo4mOjr6stc3DIOuXbuyf//+atVVvuwkJyeHsLAw13jKY4+T89VX5My8j+CZd1XrmiJS/1KOHyY4NJzwqLLvF+XPg4iIiPfLz8tleI92lfJabXO7+8fSpUu58847iY2N5a677mLp0qW1WVcFPj4+vPXWWzidTkaNGsW9997LI488Qt++fdmzZw9PP/10hfZ4r732Gt27d+e1116rs5pExPs5HHZ2blzJxqXfkLhiIXZ7KYACtYiIVJvboXrGjBkEBQWRn5/P+++/z6RJk2jbti2PP/74RftW10RCQgJr165l5MiRfPrpp/y///f/aNasGR988AF/+tOfav1+ItK45edms+qbTzm8ZwcALdrEYTG0K6KIiLjH7eUfULa5y5dffsl7773H8uXLcTgcrhmefv36ceedd3LrrbcSExNTawU3JBdb/nHydw+St3gxuT+7naD7tQ26SEOTdHg/29ctx15qw88/gIGjJ9GyXQdPlyUiInWgvpZ/1ChUnys1NZUPP/yQDz74gJ07y3YdMwwDq9XKpEmTuOOOO7j22msbVUu6C4Xq7PnzOfXnJwEwDQPnw49jTrnGk2WKyFkOu50dG1Zw/Mc9AETHtmbQ2MkEBYd6uDIREakrXheqz/XDDz/w3nvv8dFHH5GcnFx2o7Pt6jIzM2v7dh5zfqguTU3l0Ljx4HS6zjEtFhwffgUxzT1XqIgAYDqdrFn0ORmpyXTrP4Ru/YZgsWjJh4hIY9bgH1S8lF69evHiiy9y4sQJvv/+ewYNGoRpmlXaStyb2Y4drxCoAQynEyM5yUMViYhpmjjP/n9pWCwMHjuFUVN+Ro8BwxSoRUSk1tRZn+pTp04xb9483n//fXbv3l1Xt2lQ/OLag8VSaababK2tzEU8odRWwra1S/EPDKLfsASgrA91YHCIhysTEZHGplZDdVFREV988YXrwUWn00n56pIBAwYwc+bM2rxdg+MbG0vLZ+Zw6smnwDTL1lQ/9JiWfoh4QGZ6KokrFlKYl4thWOjUsz8hYRGeLktERBqpWgnVS5cu5f333+fLL7+koKDAFaTbtGnDjBkzmDlzJt27d6+NWzV4EdOnk79mLXmLF5N3wwyC9JCiSL0yTZNDP2zjh83rME0nQSFhxCdMUaAWEZE65Xao/uGHH3j//feZN28eKSkpQNlfZiEhIVx//fXMnDmTcePGNclNFCyBgQCY+ohZpF6VFBWyZfUSTp88BkDruM70HzkeP/8AzxYmIiKNntuhuk+fPhiGgWmaWCwWxo0bV2/blouInM80TdYs/Jzc7DNYrFb6DBlDh269m+Q/7EVEpP7VaPlHz549ueOOO7j99ttp2bJlbdUkIlJthmHQfeAw9m5ZR/y4qYRHNc5Np0REpGFyO1Rv3bqV/v3712YtIiLVUlSQT2F+Ls1atAKgdVwnWrbrgMVi9XBlIiLS1LgdqhWoRcSTUpOOsmX1EgDGXzfD1SZPgVpERDyhzvpUi4jUBafDwZ4t6zj4wzYAwqNicDocHq5KRESauiqF6meeeQaA6OhofvWrX1UYq66nnnrKrfeJiBTk5pC4ciFZ6acBuKJHP3rFj8Rq1fyAiIh4lmGWN5W+BIvFgmEYdO3alb1791YYqy5HI5pRys3NJTw8vNJe8imPPU7OV1+RM/M+gmfe5bkCRRqRk0d/ZNuapdhLbfj6+TNw1JW0iuvk6bJERKSBy8/LZXiPdpXyWm2r0vTO6NGjMQyDdu3aVRoTEakPp08ex15qI6p5S+ITphAUUnffGEVERKqrSqF65cqVVRoTEalNpmm6/vHed+hYwiKacUXPvnoYUUREGhyLpwsQETmfaZoc+3EPm5Z/S/kKNR9fXzr3HqBALSIiDZLbT/esXr0aPz8/hg4dWqXzExMTKS4uZvTo0e7eUkSagFKbjR3rl5F0+AAAJ48coO0V3TxclYiIyKW5HarHjh1Ly5YtSU5OrtL5N998M0lJSdjtdndvKSKNXFZGGokrFlKQm122Q+KAYbTp2NXTZYmIiFxWjfpQVaFxSI3OF5GmwTRNjuzdye7ENTidDgKDQ4lPmOLaKVFERKShq7fmrgUFBfj6+tbX7UTEi+zatIrDe3YA0LJdRwaOnoiff4BnixIREamGenlQ8cCBA2RkZNC8efP6uJ2IeJl2nbrj4+tH36FjGTphmgK1iIh4nSrPVC9YsIAFCxZUGMvJyeHuu+++6HtM0yQ7O5s1a9ZgGAajRo1yv1IRaTRM0yQr4zRRMbEAREa3YPLNdytMi4iI16pyqN6xYwfvvPMOhmG41kYXFRXxzjvvVOn9MTExzJ49260iRaTxKC4sYMuqxWSkJjNm2s1ERpd9gqVALSIi3qzKobpfv37ceeedrtfvvvsugYGB3HTTTRd9j8ViISwsjF69evGzn/2MiIiIGhUrIt7tdPJxtqxcTElxIVYfHwrzclyhWkRExJtVOVRfe+21XHvtta7X7777LuHh4cydO7dOChORxsPpdLB320Z+3LkZgLDIaOLHTSUsIsrDlYmIiNQOt7t/rFixAj8/v9qsRUQaocK8XBJXLiIz7RQAHbr1oc+Q0Vh96q35kIiISJ1z+2+1MWPG1GYdItJIJR87RGbaKXx8/Rg46kpad+js6ZJERERqnaaKRKROderVn+KiAjp270NwaLinyxEREakTVQrV48aNA6B9+/auNdTlY9VhGAbLli2r9vtExHvk5WSxb9sGBoy8Eh9fXwzDoHe82mmKiEjjVqVQvXLlSgC6detWaaw6DMOo9ntExHucOLiP7euX47CX4h8YRN+hYz1dkoiISL2oUqgu7y8dHR1daUwqcxYVAWAU5Hu4EpH6YS+1sWPDCk4c3AdAdMs2dOk9yMNViYiI1B/DLN/JRaotNzeX8PBwcnJyCAsLAyB7/nxO/flJAEzDwPnw45hTrvFkmSJ1KicznU3LF5KfkwWGQfd+Q+jWLx7DYvF0aSIiIuTn5TK8R7sKea0u6EHFWlSamsqpp36awTdME8srL+AYNBRitMGFND4pxw+TuGIhToeDgKBgBo+dQkzLNp4uS0REpN4pVNci27Hj4HRWGDOcTozkJEyFammEIqNb4OPrR1SrWAaOnoh/QKCnSxIREfEItz+ftdlsnDhxgtTU1ErH8vPzeeSRR+jbty8DBgzgySefpOjsOuPGzC+uPZz3kbdpsWC2buuhikRqX2FeruvngcEhJEy7hWFXXqNALSIiTZrbofqtt96iQ4cOPPHEE5WOXXXVVbzyyivs3r2bHTt28D//8z9MmTKFxr582zc2lpbPzIGzXU5Mw8D50GNa+iGNgmma/LhrC4s/e4fkY4dc48Fh4ersIyIiTZ7boXrx4sUA3HbbbRXGv/76a9asWYNhGMyYMYNZs2bh6+vLmjVreP/992tWrReImD6d0IkTAci7YYYeUpRGoaSokPVLFvDD5rWYppPTJ495uiQREZEGxe1QvW9fWeusgQMHVhifN28ehmHw6KOP8v777/Pmm2/yj3/8A9M0mTdvXs2q9RKWwLKPwc3gEA9XIlJz6SlJLPvqQ06fPIbFaqX/iPH0HzHe02WJiIg0KG6H6vT0dIKCgoiMjKwwvmLFCgBmzZrlGrvjjjsA2Llzp7u3E5F65nQ62bt1A2sWfU5xYQGhEVEkXHMrHbr11nIPERGR87jd/aOgoIDAwIoPJh07doz09HTatWtHhw4dXOPBwcFERESQmZnpfqUiUq8yUpPZv2MTAO279KTv0LH4+Pp6uCoREZGGye1QHRUVRXp6OtnZ2URERACwfPlyAIYPH17pfLvdTkiIlkOIeIvmrdrSpc8gwqOiaXtFN0+XIyIi0qC5vfxjwIABALz99ttA2UfFb7/9NoZhkJCQUOHc9PR08vPziY2NrUGpIlKXnA4He7asp6gg3zXWa/BIBWoREZEqcDtU33XXXZimyWOPPcaUKVOIj49nw4YNhISEcOONN1Y4d82aNQB07969ZtWKSJ3Iz81m5X8/5cDORDav+q7Rt78UERGpbW4v/7jppptYvHgxc+fOdbXXCwgI4I033nAtByn3ySefXHAGW0Q87+SRA2xbuwx7qQ0//wA69eyvBxFFRESqqUbblL/99tvcfffdrF+/noiICCZMmFDhAUUo23kxPDycmTNnMnXq1BoVKyK1x24vZdfGVRw78AMAzVq0YvDYKQSFhHq4MhEREe9To1ANMGLECEaMGHHR435+frz55ps1vY2I1KLCvFzWL1lAbvYZALr2i6d7/6FYLG6vCBMREWnSahyqRcT7+AUEYmLiHxjE4LGTad6qnadLEhER8Wq1EqptNhvff/89W7ZsIS0tDcMwiImJYfDgwUyYMAE/P7/auI2I1ECpzYaPry+GYeDj68vQCdPw9fMjIDDY06WJiIh4vRqH6jfffJMnn3ySjIyMCx6Pjo7mueee45577qnprUTETVnpp0lcsZC4rr3o2ncwAKHhkZd5l4iIiFRVjUL1o48+yssvv+xqv9W6dWvatGkDwMmTJ0lOTiY9PZ377ruPw4cP88ILL9S8YhGpMtM0ObxnO7s3r8V0Ojn24x469eyP1Ucrv0RERGqT208lrVq1ipdeegnTNPnZz37G3r17SUpKYsOGDWzYsIGkpCT27dvH9OnTMU2Tl156ydWvWkTqXklxERu+/5pdm1ZjOp20iutEwjW3KFCLiIjUAbdD9euvvw7AL37xCz777DO6dau861rXrl359NNP+cUvfoFpmrz22mvuVyoiVZaRmsyyLz8kNekoFquVvsMSGDLuKvz8AzxdmoiISKPkdqhev349FouFv/zlL5c997nnnsMwDNatW+fu7USkikqKCln33ZcUF+YTEh7J2Gk3c0WPvtrQRUREpA65/TlwRkYG4eHhNG/e/LLntmjRgoiIiIs+zCgitcc/MIieg0eQnZFGv+EJ+Piq+46IiEhdcztUh4aGkpOTQ3FxMQEBl/5IuaioiLy8PMLCwty9nYhcwumTx/ALCCIyuuwfuVf06KeZaRERkXrk9vKPPn364HA4+M9//nPZc//zn/9gt9vp27evu7cTkQtwOh38kLiGdYu/InHFQkptNgAFahERkXrmdqieMWMGpmny+9//nrfffvui57311lv8/ve/xzAM7rjjDndvJyLnKcjLYdV/P+PH3VsBaNG6nbYZFxER8RC3l3/cddddvP/++6xatYp7772XZ555hoSEBFq3bo1hGCQlJbFixQqSk5MxTZOxY8dy55131mbtIk1W8tGDbFv7PaU2G75+fgwYeSWtO3T2dFkiIiJNltuh2mKxsGDBAu6++26++OILkpKSeP/99yucU74pzM9+9jPefvttfSQtUkNOh4OdG1dxdP8uAKJiYhmcMIXg0HAPVyYiItK01WgXiLCwMObPn8/mzZv5+OOP2bJlC2lpaQA0b96cQYMGccsttzB48OBaKVakqTMsFgrycgDo0mcQPQYOw2KxergqERERqZWt1QYPHqzgLFKHnE4nFosFwzAYNGYSOWfSadGmvafLEhERkbOqHarT09N555132Lx5M7m5uURFRTF06FDuvPNOwsP1ETSAs6gIAKMg38OViLezl9rYsX4FhsXCwFFXAhAQGESAArWIiEiDUq1QvWjRIm655Rby8yuGxU8++YTnnnuOBQsWMGzYsFot0Ntkz59P3uLFAIR+8SHOuHaYU67xcFXijbLPpJG4YhH5OVlgGHTuNYCwyGaeLktEREQuwDDLnya8jKSkJHr27OkK1BaLhWbNmpGRkeF6ILFFixbs3buXyMjIuqu4AcnNzSU8PJycnBzCwsIoTU3l0Ljx4HS6zjEtFhwffgUxl995UgTKHvA9sm8XuxNX43Q4CAwOYfDYKUTHtvZ0aSIiIl4nPy+X4T3aufJaXalyU9vXXnuN/Px8wsLCeOuttygoKOD06dPk5eXx4osv4u/vT1paGnPnzq2zYhs627HjFQI1gOF0YiQneagi8Ta2kmI2LfsvOzeswOlwENuuI+Oum6FALSIi0sBVOVQvXboUwzB46aWXuPvuu/H39wcgKCiIRx55hMceewzTNFm6dGmdFdvQ+cW1h/M23zAtFszWbT1UkXgT0zRZ+92XpBw/jGGx0GfIGIZNmIZ/QKCnSxMREZHLqHKoPnLkCAC33XbbBY/ffvvtFc5rinxjY2n5zBw424/bNAycDz2mpR9SJYZh0GPAUILDIhg77WY69eqv3u4iIiJeosoPKubm5hIdHU1wcPAFj3fo0AGg0kOMTU3E9Onkr1lL3uLF5N0wgyA9pCiXUFxUQH52FtEt2wAQ27YDzVu1w2JV72kRERFvUuVQbZom1kv8RW85u+zBed6a4qbIElj2cb0ZHOLhSqQhS0s5weaV3+F0OBh33W2uXREVqEVERLxPrWz+IiJV53Q62bdtIwd2JgIQFtEMp8Ph4apERESkJqoVqvPz83nmmWdqdM5TTz1VnVuKNCqF+XlsXrmIM6dTAIjr2os+Q8fg4+Pr4cpERESkJqoVqgsKCpgzZ85FjxuGcdlzFKqlqUo5fpitq5dQaivBx9ePASPH06ZjV0+XJSIiIrWgWqG6ivvEiMgFpCWfoNRWQkR0C+ITphASFuHpkkRERKSWVDlU6wFEkeozTdPVFq93/CiCQkLp1LO/HkYUERFpZKrcp7oh2Lx5M1OnTiUyMpLg4GDi4+OZN29eld+/du1afv/73zNw4ECaNWtGQEAA3bp149FHHyU7O7vuCpcm6cSh/WxY+g3m2X+QWn186NJnkAK1iIhII+Q13T9WrlzJpEmT8PPz45ZbbiE8PJwvvviCGTNmcOzYMZ544onLXmP69OlkZGQwcuRIZs6ciWEYrFy5khdffJHPP/+c9evX07y5NmqRmrGXlrJzwwqOH9wLwPGDe4nr2svDVYmIiEhd8opQbbfbmTVrFoZhsHr1avr37w/A7NmzGTZsGLNnz+bGG2+kc+fOl7zOQw89xMyZM2nZsqVrzDRNHnjgAf7v//6POXPm8Prrr9fpr0Uat5zMDBJXLCQvOxOAbv2H0K5zDw9XJSIiInXNK5Z/LF++nMOHD3Pbbbe5AjVAaGgoTz75JHa7nblz5172Oo8++miFQA1lHUuefPJJAFatWlW7hUuTYZomR/fvZsXXH5GXnUlAUDCjpvyMHgOGuTZGEhERkcbLK2aqV65cCcDEiRMrHSsfq0kg9vUt6xHs4+MVvx3SAO3Zup4fd24GoEWbOAaOnkhAYJCHqxIREZH64hUp8uDBgwAXXN4RGRlJdHS06xx3/Oc//wEuHNpFqqJtx64c2buTbv2H0LnXAFfHDxEREWkavCJU5+TkABAeHn7B42FhYZw8edKta+/YsYM5c+bQvHlz/vjHP17y3JKSEkpKSlyvc3Nz3bqneD/TNMnKOE1UTCwA4VHRTL75bvz8AzxcmYiIiHhCk17sefToUa6++mocDgcff/wx0dHRlzz/+eefJzw83PXVtm3beqpUGpKS4iLWL1nAqm8+cW03DihQi4iINGFeEarLZ6jLZ6zPl5ube9FZ7Is5fvw4CQkJpKenM3/+fBISEi77nscff5ycnBzXV1JSUrXuKd4v/dRJln35AadPHsOwWCjI06cVIiIi4iXLP8rXUh88eJCBAwdWOJaVlUVGRgbDhw+v8vWOHTtGQkICKSkpfPbZZ1x99dVVep+/vz/+/v5VL1waDdPpZP+ORPbt2ASmSWh4JPHjphIeFePp0kRERKQBqLWZatM0ycjI4MSJE7V1SZcxY8YAsGTJkkrHysfKz7mcY8eOMXbsWJKTk/nkk0+49tpra69QaZSKCvJZs+hz9m3fCKZJu849SLj2NgVqERERcalxqN62bRs33HAD4eHhtGjRgo4dO1Y4npWVxS9/+Uvuu+8+bDabW/cYP348HTt2ZN68eezYscM1npeXx7PPPouPjw933XWXazwjI4P9+/eTkZFR4TrnBuqPP/6Y66+/3q16pGk5deIwGanJ+Pj6MmjMJAaNnojP2TaMIiIiIlDD5R/vv/8+s2bNorS09KLnREZGcvToUZYtW8a0adO46qqrql+kjw9vvfUWkyZNYtSoUdx6662EhYXxxRdfcPToUZ577jm6dOniOv+1115jzpw5zJ49m6effto1PnbsWI4fP87QoUPZtWsXu3btqnSvc893l7OoCACjIL/G1xLP69CtD4X5ebTv0pPQ8EhPlyMiIiINkNuhet++fdxzzz2Ulpby29/+lpkzZzJ58mTOnDlT6dyZM2eydOlSFixY4FaoBkhISGDt2rXMnj2bTz/9FJvNRs+ePXn22WeZMWNGla5x/PhxADZu3MjGjRsveE5NQ3X2/PnkLV4MQOgXH+KMa4c55ZoaXVPqV0FuDnu2rqP/iAn4+vlhGAa9Bo/0dFkiIiLSgBmmaZruvPGee+7h7bff5oEHHuB///d/AWjZsiVpaWk4HI4K56akpNCmTRt69uzJ7t27a151A1HedSQnJ4ewsDBKU1M5NG48OJ2uc0yLBceHX0FMc88VKlV28uiPbFuzFHupjbiuvRgwcoKnSxIREZEayM/LZXiPdq68Vlfcnqlevnw5hmHw6KOPXvbcVq1aERQUVCcPMTYktmPHKwRqAMPpxEhOwlSobtAcdju7Nq3i6P6yf/RFNW9Jt37xHq5KREREvIXboTolJYXg4GDatGlTpfMDAwMv2me6sfCLaw8WS6WZarO1NolpyHKzM0lcvpDcrLIHW7v2HUz3AUOxWKwerkxERES8hdvdP/z9/bHZbFRl9UhRURHZ2dnV3qDF2/jGxtLymTlgGACYhoHzoce09KMBO33yOCsWzCM3KwP/wCBGTL6enoNGKFCLiIhItbgdquPi4igtLeXgwYOXPXfhwoU4HA569Ojh7u28RsT06YROnAhA3g0z9JBiAxfeLAYfXz+at2rH+Otm0KJ1e0+XJCIiIl7I7VA9efJkTNPkn//85yXPO3PmDH/84x8xDMPtzh/exhIYCIAZHOLhSuRCCs/ZWjwgMIixV9/MiMnXExAU7MGqRERExJu5HaofeughQkJCeOONN5gzZw55eXkVjhcVFTFv3jwGDRrE0aNHadasGffdd1+NCxZxl2maHNqznSXz3yXp8H7XeHBYOMbZJTsiIiIi7nA7VLdo0YJ58+bh6+vLM888Q0xMjKtHdc+ePYmKiuKOO+7g+PHj+Pv789FHH9VpGxORS7GVFLNx6Tfs2rgKp9NBatIxT5ckIiIijUiNtim/+uqrWb16NQMHDsRms2G32zFNk3379lFSUoJpmvTv35/Vq1czfvz42qpZpFoyUpNZ9uWHnDpxBIvFSt+hYxk0ZpKnyxIREZFGpEbblAPEx8eTmJjIrl27WLt2LSkpKTgcDmJjYxkxYgSDBg2qjTpFqs00TQ7s3My+bRswTZPgsAjiE6YSGa1uLCIiIlK7ahyqy/Xp04c+ffrU1uVEaiwz7RR7t64HoO0V3eg3fBy+fn4erkpEREQao1oL1SINTbMWrejWfwhBIWG079xDDyOKiIhInVGolkbD6XSwf0ci7Tv3IDi0bKOhHgOGebgqERERaQrcDtXjxo2r9nsMw2DZsmXu3lLkogrzcklcuYjMtFOkJZ9gzNU3aWZaRERE6o3boXrlypVVOq882JimqZAjdSL52CG2rfmeUlsJPr5+dOrVX3/WREREpF65Hapnz559yeM5OTls2rSJDRs20KxZM+6//36sVqu7txOpxGG3sztxDUf27QQgMqYF8QlTXUs/REREROpLnYXqcsuXL+eGG25g7969zJ8/393biVRQVJDP+iULyMlMB6Bz74H0HDgci/7hJiIiIh5Qo81fqmLcuHH885//5Msvv+Stt96q69tJE+HnH1D2Y0AgwydeS+/4UQrUIiIi4jF1HqoBbr75ZqxWq0K11Ii9tBTT6QTA6uPDkPFXMf66GcS27eDhykRERKSpq5dQHRAQQHBwMPv27auP20kjlJOZzvIF89i3Y5NrLCQsgsDgEA9WJSIiIlKmXkJ1cnIyOTk5mKZZH7eTRsQ0TY7s28mKrz8mPyeL4z/uxV5q83RZIiIiIhXU+eYvRUVF/OpXvwKgd+/edX07aURsJcVsW7uUlGOHAGjRJo5Boyfi46utxkVERKRhcTtUP/PMM5c8XlxcTFJSEosXL+bMmTMYhsEDDzzg7u2kiclMO0XiikUU5udiWCz0GjRS/adFRESkwXI7VD/99NNVCjimaWKxWPjTn/7Ebbfd5u7tpAmxlRSz9rsvsZfaCAoNIz5hKlExsZ4uS0REROSi3A7Vo0ePvmSo9vHxITIykr59+3LTTTfRuXNnd28lTYyffwC940eRlnKCASMn4Ovn7+mSRERERC6pzrcpF6mKtJQkfHx8iGreEoC4rr2I69pLyz1ERETEK9T5g4oil+J0Otm/fRP7d2wiMDiU8dfPwM8/QGFaREREvIrbLfUsFgs+Pj4cOnSoNuuRJqSwII81Cz9n/9ne081bt9OuiCIiIuKV3J6pDgwMxNfXl06dOtVmPdJEnDpxhK2rl2ArKcbH14/+I8bR9opuni5LRERExC1uh+o2bdpw8uTJ2qxFmgCn08kPiWs4tGc7ABHNmhM/biohYRGeLUxERESkBtxe/nHVVVdRXFzMqlWrarMeaeQMw6AgLweAK3r2Y8y0mxSoRURExOu5Haoff/xxYmJiuP/++zl16lRt1iSNkNPpBMpC9cDRExl25bX0HToWq1XPyoqIiIj3czvR7Nu3j7/85S889NBD9OjRgzvuuIMRI0bQvHlzrJd42Gz06NHu3lK8kN1eyq4Nq7DbSxk8djKGYeDnH0DLdh08XZqIiIhIralyqH7vvfcIDAzkxhtvBGDs2LEV2p69/vrrvP7665e8hmEY2O12N0sVb5ObdYbE5QvJzT4DQOfeA4mMbu7hqkRERERqX5VD9V133UXLli1doRrKtiCvjuqeL97JNE2O/biHXRtW4nDY8Q8MYvDYKQrUIiIi0mhVa/nHuaG4fI2syLlKbSVsX7eMk0d+BMp6Tw8aM5mAwCAPVyYiIiJSd/SUWB1wFhUBYBTke7iS+mWaJuuXfM2Z08kYhkGPgcPp0meQdkcUERGRRs/t7h9yYdnz55O3eDEAoV98iLHoaw9XVH8Mw6D7gKEEhYYx+qob6dp3sAK1iIiINAkK1bWoNDWVU0/Ndr02TBPLKy9AepoHq6pbJcVFpJ9Kcr1u3qotE392J81atPJgVSIiIiL1S6G6FtmOHYfz1pobTidGctJF3uHdMlKTWfblh2z4/mvyc7Jc45ZLtFQUERERaYyqtab69OnTl+xBfTmNvaWeX1x7sFgqBGvTYsFs3daDVdU+0+lk/87N7Nu+EUyTkPBIHA6Hp8sSERER8Zhqz1Sbplmjr8bMNzaWls/MgbPriE3DwPnQYxDTeFrJFRXks/a7L9i3bQOYJu06dWfctbcSHhXt6dJEREREPKZaM9XBwcH8/ve/r6taGoWI6dPJX7OWvMWLybthBkFTrvF0SbUm9eQxtq5aTElxEVYfX/oNT6B95x6eLktERETE46oVqkNCQpg9e/blT2ziLIGBAJjBIR6upHalpyRRUlxEeFQ08QlTCY2I8nRJIiIiIg2C+lRLlfUcOBz/gECu6NEPq4/+6IiIiIiUU/cPuajkowdZt/grnM6yhxAtVitd+gxSoBYRERE5j9KRVOKw29m1aTVH9+8C4Oj+3VzRo59nixIRERFpwBSqpYK87EwSVywkJzMDgC59BtGhW28PVyUiIiLSsClUi8vxg3vZsX45Drsd/4BABo2ZRIs2cZ4uS0RERKTBq3Kodp63U6A0Lvu2byrrPQ3EtGzLoLGTCQwK9nBVIiIiIt5BM9UCQJuOXTj0w1Y69xpI176DMSx6hlVERESkqhSqmyjTNMnKOE1UTCwAoeGRTLrpbvz8AzxcmYiIiIj30XRkE2QrKWbTsv+y8ptPSD+V5BpXoBYRERFxj2aqm5gzp1NIXLGIooI8DIuFgrxcYlp6uioRERER76ZQ3USYpsmPu7awd+t6TNMkODSc+HFTiYxu4enSRERERLyeQnUTUFxUwJZVi0lLPgFAm45d6T9iHL5+/h6uTERERKRxUKhuAk4nHSMt+QRWqw99h42lfZeeGIbh6bJEREREGg2F6iagXece5Odm0/aKboRFNvN0OSIiIiKNjrp/NEKF+XkkLl+IraQYAMMw6DlohAK1iIiISB3RTHUjk3L8MFtXL6HUVoLFamXQmEmeLklERESk0VOobiQcDjs/JK7l8N4dAEREt6B7/6GeLUpERESkiVCobgTyc7JIXLGI7DNpAHTqNYBeg0ZgsVo9XJmIiIhI06BQ7eXSTyWx4fuvsZeW4ucfwMDRk2jZroOnyxIRERFpUhSqvVx4VAy+fgFENGvOoLGTCQoO9XRJIiIiIk2OQnUdcBYVAWAU5NfJ9QvzcwkMDsUwDPz8Axh91XSCgkMxLGrmIiIiIuIJSmG1LHv+fPIWLwYg9IsPMRZ9XWvXNk2TI/t3sWT+uxw/uNc1HhwarkAtIiIi4kFKYrWoNDWVU0/Ndr02TBPLKy9AelrNr20rIXHFQnasW47T4SA16Simadb4uiIiIiJSc1r+UYtsx46D01lhzHA6MZKTMGOau33dzPRUElcspDAvF8Ow0HPwCDr3GqCtxkVEREQaCIXqWuQX1x4slgrB2rRYMFu3det6pmly6Idt/LB5HabpJCgkjPiEKUQ1b1lbJYuIiIhILdDyj1rkGxtLy2fmwNkZZNMwcD70GLg5S519Jp3diWswTSetO3Rm3HW3KVCLiIiINECaqa5lEdOnk79mLXmLF5N3wwyCplzj9rUio5vTY+Bw/AIC6NC1t5Z7iMj/b+/Oo6K48j2Af5utG5odRIwMoLhEUIO4ROOCuASjjpoTDW7RoGA0Jo4MiTOaIJA4iaLjMyaZ524SjbvZXkxcCOCuD6IYjVGIgg9GUVAWQdma3/uDqUq3vdDQ1ay/zzl1DtStuvXrulXdv66uupcxxlgzxUm1GVjY2gIASGlfr/WopgbXf0mDV6eusHdyAQA8HThA8vgYY4wxxpi0+PaPZuJxWSlOHv4KV38+g/9N/hE1TzzwyBhjjDHGmi++Ut0M5OVkIe3EUVSWP4aVtTW69AyCBfc7zRhjjDHWYnBS3YRqVCr8mnYamVcuAACc3Nrh2ZCx4q0fjDHGGGOsZeCkuomUP36Es8e+RWH+XQCAn38geg4YAktLbhLGGGOMsZaGM7gmYmMjBwBY28jRd+hoPOXbpYkjYowxxhhjDdWibtxNTU3F2LFj4eLiAqVSiQEDBmDXrl31qqOmpgaffPIJevfuDVtbW7Rr1w4vv/wyMjMzzRT1H1TV1aipUQEALCwt8WzIOIx8cQYn1IwxxhhjLVyLSapTUlIwZMgQnDx5EpMnT8aCBQtQUFCAGTNm4IMPPjC6nvnz5+PNN9+ESqXCm2++ibFjx+K7775D//79cfXqVbPFX1J4H8nf7cbVtDPiPDsHR9jZO5ptm4wxxhhjrHG0iNs/qqurERERAZlMhhMnTqBPnz4AgNjYWAwaNAixsbGYMmUKunbtarCe5ORkbN68GUOHDsWxY8cgl9fegjFr1iyMHj0aCxYswPHjxyWNnYhwK/MqLp1JhkpVjYryx+j2TH/YyBWSbocxxhhjjDWdFnGlOikpCTdu3MD06dPFhBoAHBwcEBMTg+rqamzfvr3OejZv3gwAWLFihZhQA8DIkSMRGhqKEydOICMjw+R4K/PyAACUk42044dx4eQxqFTV8HjKGyMnzeCEmjHGGGOslWkRSXVKSgoA4Pnnn9cqE+YZc4U5JSUFSqUSgwcP1ioLDQ01uh5DsqdOw+Nz51Do4oIzSkvk3LgOmUyGgH7PYfCYF6GwU5pUP2OMMcYYa35axO0fwkOEum7vcHFxgbu7e50PGpaVleHOnTvo2bMnLC0ttcqFug3VU1FRgYqKCvH/kpISjfKHySl4nJ6OKisrHA8Zjkq5HLZlZRgQEAS3Z3i4ccYYY4yx1qpFJNXFxcUAACcnJ53ljo6OyM3NNbkO9eV0+fDDDxEfH6+3vPQ/V7mtq6vR58IF5Hr9Cf3+939RWWGJO/2GG4yPMcYYY4xJr6y0vFG20yKS6uZi6dKl+Otf/yr+X1JSgj/96U/i//bBwSjaswcA4JN9C97ZtyAD4PHCCHTxdW3scBljjDHG2rySksZJd1tEUi1cXdZ3FbmkpETvFej61KG+nC5yuVzjAccnOYQMh21gIB6npwMAZABsAwPx1JjRBmNjjDHGGGPmYaWyaZztNMpWTKR+v3Pfvn01ygoLC1FQUIDnnnvOYB1KpRIdOnRAVlYWVCqV1n3Vhu7brg/fPbvxMDkFpSdOwH7YMDiEDDepPsYYY4wx1vy1iKQ6ODgYH374IY4ePYqpU6dqlB09elRcxph69uzZg9OnT2PYsGEaZUeOHDG6HgERAdB+YBF9g6DsGwTSVcYYY4wxxhqNkIsJeZvZUAtQVVVFnTt3JrlcThcvXhTnl5SUUEBAAFlZWdH169fF+fn5+fTbb79Rfn6+Rj1JSUkEgIYOHUoVFRXi/MTERJLJZDRs2LB6xZWTk0MAeOKJJ5544oknnnhq5tONGzcalogaSUZk7rRdGsnJyQgNDYVcLse0adPg6OiIr776CllZWVixYgXeeecdcdm4uDjEx8cjNjYWcXFxGvVERkZiy5Yt8Pf3x7hx43D37l3s3bsXCoUCZ86cgb+/v9Ex1dTU4Pbt23BwcIBMJhPnCw8w5uTkiL2KsNaJ27rt4LZuO7it2w5u67ahuLgY3t7eKCwshLOzs9m20yJu/wCAkJAQnDp1CrGxsdi3bx8qKysREBCA999/HzNmzDC6no0bN6J3797YuHEj1q9fD3t7e/z5z3/GP/7xD3Tr1q1eMVlYWMDLy0tvuaOjI5+kbQS3ddvBbd12cFu3HdzWbYOFhXnHPGwxV6pbEqE3kuLiYj5JWzlu67aD27rt4LZuO7it24bGaucWMUw5Y4wxxhhjzRkn1WYgl8sRGxtrsE9r1jpwW7cd3NZtB7d128Ft3TY0Vjvz7R+MMcYYY4yZiK9UM8YYY4wxZiJOqhljjDHGGDMRJ9WMMcYYY4yZiJNqxhhjjDHGTMRJtZFSU1MxduxYuLi4QKlUYsCAAdi1a1e96qipqcEnn3yC3r17w9bWFu3atcPLL7+MzMxMM0XNGsLUtj516hSio6PRt29fuLm5QaFQ4Omnn8bf/vY3FBUVmS9wVm9SnNfqqqqqEBgYCJlMhqefflrCSJkppGrnhw8fIjY2Fj179oSdnR2cnZ0RFBSE+Ph4M0TNGkKKti4qKsLy5cvRu3dvODg4wN3dHf3798cnn3yC8vJyM0XO6mPnzp147bXX0K9fP8jlcshkMnz22Wf1rkfyvMysg6C3EsnJyWRjY0P29vYUERFB0dHR1KlTJwJA//jHP4yuJzIykgCQv78/vf322zRr1iySy+Xk5OREv/76qxlfATOWFG3dvn17srS0pODgYFq8eDFFRUVRnz59CAD5+fnR3bt3zfwqmDGkOq/VxcTEkFKpJADUvXt3iSNmDSFVO9+6dYv8/PxIJpPR6NGjacmSJfSXv/yFxo0bR7169TLjK2DGkqKtCwsLqXPnzgSAhgwZQtHR0fTGG2+Qn58fAaARI0aQSqUy8ythdfHx8SEA5O7uLv69ffv2etcjdV7GSXUdqqqqyM/Pj+RyOV24cEGcX1JSQgEBAWRlZUUZGRl11pOUlEQAaOjQoVReXi7OT0xMJJlMRsOGDTNL/Mx4UrX1ypUr6fbt2xrzampqaMGCBQSAXn/9dcljZ/UjVVur+/nnn8nKyorWr1/PSXUzIVU7V1dXU//+/cnW1paSkpJ0boc1LanaetWqVQSAoqKiNOZXVFRQ//79CQAdP35c8vhZ/Rw7doyys7OJiOjDDz9sUFJtjryMk+o6HDlyhABQeHi4VtmePXsIAC1durTOeqZNm6b3ZBwzZgwBoOvXr0sSM2sYqdpan9u3bxMACggIMCVMJgGp27qiooJ69epFQ4YMoZqaGk6qmwmp2llYNiYmxhxhMglI1davvfYaAaBjx45plS1btowA0P79+yWJmUmjoUm1OfIyvqe6DikpKQCA559/XqtMmHf8+HGj6lEqlRg8eLBWWWhoqNH1MPORqq31sba2BgBYWVk1uA4mDanbOi4uDpmZmdi6dStkMpkkMTLTSdXOe/fuBQBMmTIFOTk52LBhA1auXIn9+/ejtLRUuoBZg0nV1gEBAQCAw4cPa8yvqqpCYmIibG1tMWjQIBOjZc2BOfIy/nSvg3CzeteuXbXKXFxc4O7uXucN7WVlZbhz5w569uwJS0tLrXKhbn5gsWlJ0daGbNu2DYDuN33WuKRs69TUVCQkJOCDDz5At27dJI2TmUaqdk5LSwNQ+xByVFQUKioqxLJ27dph3759GD58uDRBswaRqq0jIiKwY8cO/POf/0RaWhr69++PiooKHD58GIWFhdi1axc6duwoefyscZkrL+Mr1XUoLi4GADg5Oeksd3R0FJcxpQ715VjTkKKt9UlPT0d8fDw8PDywZMmSBsfIpCFVW1dUVODVV19Fnz59EB0dLWmMzHRStfO9e/cAAG+++SYWL16MnJwc5OfnY/369SguLsakSZNw584d6QJn9SZVW9va2iIlJQUzZ87E8ePHsWbNGnz88ce4ceMGpk+fjiFDhkgaN2sa5srLOKlmzMyysrIwfvx4qFQq7NmzB+7u7k0dEpNITEwMMjMzsW3bNp1XO1jrUFNTAwAYP348Vq5cCS8vL7i7u+PNN99EVFQUiouLsXXr1iaOkkmhoKAAo0ePxrlz53Do0CEUFRUhLy8PGzZswPbt2/Hss8+isLCwqcNkzRQn1XUQvsXo+7ZSUlKi95tOfepQX441DSna+km3bt1CSEgI8vPzceDAAYSEhJgcJzOdFG194cIFrF27Fu+88w569eoleYzMdFKd08IyEyZM0Cr785//DOCPW0RY05Cqrf/617/izJkzOHjwIMaOHQsnJye0b98ekZGRSEhIwM2bN7Fu3TopQ2dNwFx5GSfVdTB0X01hYSEKCgp03sOlTqlUokOHDsjKyoJKpdIqN3QvGGs8UrS1uuzsbAwfPhy3b9/Gvn37MH78eMliZaaRoq1/+eUXqFQqxMXFQSaTaUwAcP36dchkMjg7O0sePzOOVOd09+7dAUBnWwrzHj9+3PBAmcmkautDhw7B1dUVvXv31iobMWIEAODnn382MVrW1MyVl3FSXYfg4GAAwNGjR7XKhHnCMnXVU1ZWhtOnT2uVHTlyxOh6mPlI1dbAHwn1v//9b+zduxcTJ06ULlBmMinaulu3bpg7d67OCai9wjF37lzMmjVL4uiZsaQ6p4Vk6urVq1plwjxfX9+GhskkIFVbV1ZWoqSkBJWVlVpl+fn5AAC5XG5KqKyZMEteVq8O+Nqgqqoq6ty5M8nlcrp48aI4X71DefV+DPPz8+m3336j/Px8jXrUOxmvqKgQ5/PgL82HVG2dlZVFPj4+ZGVlRQcPHmys8Fk9SNXW+oD7qW4WpGrnmzdvklwuJw8PD8rNzdWoJzAwkABQYmKi2V8P00+qtg4NDSUA9O6772rMLy8vF8s+/vhjs74WVj919VPdmHkZJ9VGSEpKImtra7K3t6fIyEiNoU9XrFihsWxsbCwBoNjYWK16IiIieJjyZk6KthaGTB04cCDFxsbqnFjTk+q81oWT6uZDqnYWRsp0c3OjiIgIWrhwIfn6+hIAmjdvXiO9GmaIFG198eJFcnBwIAA0YMAAioqKogULFohDl/ft25ceP37ciK+K6bJ582aaPXs2zZ49m4KCgggADR48WJz39ddfi8s2Zl7GSbWRzp8/T2PGjCEnJyeytbWlfv360c6dO7WWM9R4KpWK1q9fTwEBASSXy8nNzY0mT57MIyk2M6a2NYA6J9Y8SHFe68JJdfMiVTt/9913NHToULK3tyeFQkF9+/alTZs2mTl6Vh9StHVGRgaFh4eTt7c3WVtbk62tLfXq1Yvi4+OprKysEV4Fq8vs2bMNfsaqt2tj5mUyIqL63TDCGGOMMcYYU8cPKjLGGGOMMWYiTqoZY4wxxhgzESfVjDHGGGOMmYiTasYYY4wxxkzESTVjjDHGGGMm4qSaMcYYY4wxE3FSzRhjjDHGmIk4qWaMMcYYY8xEnFQzVg/Z2dmQyWSQyWTIzs5u6nBaFV9fX8hkMnz22WcNWp/bpnXYsmULZDIZXn/99aYOhRlp+PDhkMlkiIuL01n+6NEjxMTEoEePHrC1tRXP0/T0dACmn/tPaur3gjFjxkAmkyEpKanRt82aFifVrMWLi4sT30Drmtqazz77TOd+sLGxgaenJ55//nls2bIFVVVVTR2qQXFxcYiLi2uVybKQkDw5KZVK+Pn5YerUqThy5IjZtr9u3TrExcWJCU5TKisrQ0xMDORyOZYtW6ZVXlRUhG+//RbLly/H+PHj0aFDB3F/SZWQSaGqqgrbtm3D2LFj0bFjR8jlcjg5OaFbt24ICQnB0qVL8eOPP6K8vLypQ20UYWFhWLFiBa5duwaZTIb27dujffv2sLa2bvRYsrOzxfcTcxHqfuutt1BTU2O27bDmx6qpA2BMSu3bt2/qEJotd3d3WFpaAgBKS0tx9+5dHDt2DMeOHcPGjRtx9OhRuLi4NFl8fn5+UCgUcHJy0iqLj48HUJuA+vr66lzf2toa3bt3F/9uaaytreHq6ir+f//+fdy8eRM3b97E3r17ERERgU2bNkn+5XDdunW4desWfH19ERgYKGnd9ZWQkIC8vDwsXLgQXl5eWuXffPMNwsPDmyAy4+Xk5GDs2LG4cuWKOM/GxgaWlpa4ceMGMjMzkZKSgpUrVyI5ORnDhw9vumAl4u3tje7du8Pd3V2r7Nq1a/j+++8BAHv27EFYWJjWMobO/YYw9F6QnZ0tvp+YK7EeOHAgQkNDceTIEezcuROzZs0yy3ZY88NJNWtV8vLymjqEZis1NVUjIc3KysK7776LXbt2IS0tDfPmzcP+/fubLL6ffvrJpPU7duyIa9euSRRN43vuueeQkpIi/q9SqZCeno6oqCicPHkSW7ZswcCBAzF37tymC9KMHj9+jI8//hgAMH/+fL3LeXp6ok+fPggKCkJQUBBeeumlxgqxTiqVChMnTsSVK1dgZ2eHpUuXYvbs2fDy8oJMJkNFRQV++eUX/PDDD9ixY0dThyuZL774Qm/Z5cuXAQBubm46E2rA9HP/Sc3hvWD+/Pk4cuQIEhISOKluQzipZqyN6tSpE3bu3ImcnBycPHkSBw8eRF5eHjw9PZs6NAbA0tISffv2xbfffouuXbvi/v372Lp1a6tNqvfu3YvCwkIEBgaiZ8+eOpeZOXMmXn311cYNrB6SkpJw8eJFAMDWrVsxdepUjXK5XI7+/fujf//+WL58OSorK5sizEb16NEjAIC9vX0TR9K4xo4dC1dXV/z66684ffo0Bg8e3NQhsUbA91SzNqeqqgrHjh3DokWL0K9fP3To0AE2Njbw8PBAaGgodu/eDSJqUN25ubmIiopCQEAAlEol5HI5nnrqKfTt2xdRUVFITU3Vu25KSgqmTZsGb29v8afQAQMGICEhAWVlZQ19uQbJZDLMnDkTAEBESEtL0yjPy8vD22+/jYCAANjb20OpVCIgIABLlizB3bt39dZbWFiI5cuXIygoCI6OjuI93L1798b8+fN1XpnS9bDSq6++qnG7Q0hIiMZ9x+pX3vU9nLRo0SLIZDIEBQUZ3BelpaVQKpWQyWTYuXOnVnl5eTnWr1+P4OBguLu7i69p0qRJOHz4sMG6TeHi4oJnn30WAPDrr7/qXOb69etYvXo1Ro0aBT8/P9ja2sLR0RF9+vTBu+++i4KCAq11hGcRbt26BQAIDw836hkEcx2nmzdvBgBMnz5d7zJWVs37OpD6fekTJ040uKxMJoNcLtc5XyaTISUlBXl5eXjjjTfQqVMnKBQKeHp6YsaMGUZdhTWlne7fv4/33nsPzz77LFxdXaFQKODr64vQ0FBs2LABxcXFGsvrelBROL6EL0G3bt3SOLbUvxwZ86Di+fPnER4eji5dukCpVMLR0RH+/v6YM2cOjh49qrGsvvcCX19fhISEiP8/ebwLMQ0cONCoh2V/+uknyGQyWFhY4ObNmxplNjY24q8omzZtMlgPa0WIsRYuNjaWAJCxh3NycrK4PACSy+Vkb2+vMW/KlCmkUqm01s3KyhKXycrK0ihLT08nFxcXsdzS0pJcXFxIJpOJ82bPnq1VZ1VVFUVERGhs397eniwtLcX/u3fvTtnZ2fXeN9u3b9cbr+DQoUPiMl9++aU4PyUlhZydncUyOzs7UiqV4v8uLi508uRJrfpycnLI29tbXM7CwoJcXFw0Xk9wcLDWej4+PgSAtm/fLs5btGgRtW/fXmOb7du3F6d+/fqJy+prm9TUVHH+lStX9O6rzz77TNz3paWlGmUZGRnUtWtXsR6ZTEZOTk4abbZgwQK9dRsSHBysd58IXnjhBQJASqVSZ7mw74TYnJ2dNY67jh070rVr1zTWWb16NbVv354sLCwIADk6Omrs2/bt22ssb87jtKioSIzj7Nmz9VpX2Lb6cdNUEhISxHgyMjIaVIew/rZt28jT05MAkK2trcZ7lEKhoB9//FHn+qa205EjRzTex6ysrDTeBwDQ119/rbGOcAzHxsaK84Tjy9HRUXwfUD+2Fi1aJC6r69wXVFdX06JFizS2r1Qqyc7OTvzfyclJYx197wX9+vXTeG1PHu9CTML7pqOjI5WVleltq7CwMAJAo0eP1lm+Y8cOAkAeHh5662CtCyfVrMWrb1J97tw5mj59Oh06dIjy8vKopqaGiIju379PH330kfgh8NFHH2mtayipHjlyJAGgoKAgOnv2rFhvRUUFZWRk0Jo1ayghIUGrzr/85S/iG/y//vUvun//PhERVVZWUnJyMvXp00esV1eib4gxSfWnn34qLiN8UP/f//2f+EHq7+9Pp06dEpc/ceIEde/enQCQq6sr5ebmatQ3d+5cAkC+vr6UmJhI1dXVRFT74ZidnU3//d//TX/729+04jD0wSrEl5ycrPe1Gmobf39/AqBzuwKh/WbNmqUxv7CwkHx9fQkAjRgxgk6cOEHl5eVEVJsMrl27Vkx41q1bp7d+fepKqh88eEBubm4EgHr16qVzmbCwMPr444/p999/p4qKCiKqPe4SExNpwIAB4vGji6H9rs6cx+n3339PAMja2poeP35cr3WbU1KdkpIixjNixAitc8MY6omit7c3HT16VHwvOX/+PPXq1UtM+HJycrTWN6WdLly4QAqFggBQQEAA/fDDD1RZWUlERGVlZZSamkrR0dGUmJiosZ6upFogvAf5+Pjofc2GjsElS5aI+2TOnDl0/fp1sezu3bv0zTffUFhYmMY6ht4L1C+q6PPo0SMx+d62bZvOZfLz88nGxoYA0IEDB3Quk5GRIW7rt99+07s91npwUs1aPPWk+skrD+qToauU6vbv308AyM/PT6vM0Ju1ra0tAaAzZ84YHfvly5dJJpORnZ0d/fLLLzqXKSkpIS8vL51XiOpSV1JdVVVFzzzzjHglqaCggIiI5s+fL14ZvnPnjtZ6OTk54pePhQsXapT16NGDANCuXbvqFas5k+oPP/yQAJCXl5fOhC83N1e8UvpkwvDWW2+JSVJVVZXObX/11VcEgNzd3fUuo4++pLq6uprS0tJo6NCh4utau3ZtveomInr48KF4tV/XLwvGJNXmPk5jYmIIAPXs2bNe6xE1r6SaiGj06NFiTJaWljRo0CBavHgx7dixw6ir18K6NjY2dPXqVa3yu3fvkqurKwGg119/XaPM1HYaMmQIAaCuXbtSUVGR0a/ZXEn19evXxfNyyZIlRsdjalJNRLR48WICQAMHDtRZvmbNGvEzR/jioYvwhVtfcs5aF76nmrUqd+/e1TsZ2xfzuHHjAAA3btzAnTt3jN62s7MzANRrna1bt4KIMG7cOPTq1UvnMg4ODpg0aRIASNZfcWlpKc6dO4exY8fi0qVLAIDZs2fDzc0NRIR9+/YBqH2CXdeDi15eXmIPDXv27NEoa8h+MLeZM2fCwsICubm5SE5O1ir/8ssvUVNTAy8vL417LokI27ZtAwBER0frvad30qRJcHR0REFBAX7++ecGxXjmzBl4enqKk0KhQL9+/XDy5EkAwEsvvYQ33nij3vXa29sjODgYAHDq1KkGxWbu4/T27dsAgHbt2jUovubk66+/xuuvvw5ra2uoVCqcPXsW69atwyuvvIJu3brB19cX8fHxKCkpMVjPlClT0KNHD635Hh4e4rm3d+9ejTJT2ikzM1M8Pj744APJurczxeeff46amhq4ubmJ3eA1FmEfnzt3TuzBRN2WLVsAAHPmzDHYhaebmxuAP45x1rpxUs1aFar99UXnpN4H78OHD7F69WoEBwfDw8MDNjY24sMqdnZ24nL//ve/jd72+PHjAdQmp9HR0Th+/Lj45Ls+wofYjz/+qJFQPTlt374dAMSHyhqiU6dO4mt0cHDAoEGDcOzYMQDAqFGjxO7MsrKy8ODBA3G+PqNHjwZQ+1BTVlaWOF/YD3//+98xb948HD58uM4Ewty8vLzE/oB1dWUmzJsxYwYsLP54W7x69aq4L1599VW97dOhQweUlpYCaHgbVVVVaXwJrK6uBlD7MNWnn36KAwcOGPzw/v777xEWFobOnTuLD1wKk/AlKTc3t0Gxmfs4zc/PBwCNfrpbKqVSiU8//RS5ubnYtGkTXnnlFfTo0UPsI/7WrVuIi4tDYGAgbty4obeeESNG1Fn25LlnSjudOXMGQG2vMy+88EIDX720hJhGjx4NhULRqNvu3r27+AVbeIhWcPLkSXEgm4iICIP1CMe0cIyz1q15P0rNmBlkZGRg5MiRGgmGnZ0dnJ2dxYRK6NmiPr0ZJCQk4Pfff0dycjLWrl2LtWvXwtLSEoGBgRg3bhzmzZuHjh07aqwjXL0oLS0VkzJD6krSDVEf/EUYaKR3796YPHkyJkyYIPb2cO/ePXGdJ+NVpz44x71799CpUycAwNtvv41Lly5h37592Lx5MzZv3gyZTIaAgACMGTMGkZGR6NatW4NfR0PNmjULSUlJOHjwIP71r3+JX57S09PFgTqe7E9W/eqSsR+KDW2j4OBgsZ/qqqoq3Lp1C5s2bcKaNWuwZMkSBAQEiFec1dXU1GDmzJnYvXu3OM/KygouLi6wsbEBABQXF6O8vLzBvXOY+zgVRhbU1RtGY9HXlWRYWBg++uijetfn4eGByMhIREZGAqjdd0lJSVi9ejVOnTqFrKwsTJ06VW+PQIbOPfUy9XPPlHYS+vh3d3eHUqmsc93GIMTk4+PTJNufP38+kpOTsWPHDqxatQq2trYA/ujNY/To0ejcubPBOoR12sromW0dX6lmbU54eDhyc3Ph6+uL/fv34/79+ygrK8O9e/eQl5encXWa6tG1nrOzM5KSknDy5EksWbIEgwcPhpWVFX7++We899576Nq1q0biA9QOFgEAK1euNHiVXZjUBwepr9TUVOTl5SEvLw85OTm4dOkSduzYgYkTJ+rtPs3Y0fvUl7O2tsbevXuRnp6O5cuXY8SIEbCzs8OVK1ewZs0a+Pv745///GeDX0dDvfTSS7Czs0NpaSm+/vprcb5wlbpv377w9/fXWEdoH6D2A96YNpKiH2Vra2t06dIFCQkJiI2NRVlZGV5++WWNLzyCrVu3Yvfu3bC0tMTy5cuRmZmJiooKPHjwQGzvyZMnA6jf8azO3Mep8BN5YWFhg+KTgr7bxp7sPq6h7O3tMWHCBBw/fly8ApqWlqZ3ePiGjJwpRTtJPWKnFJoqphdffBGenp4oKioSB8YqKirCgQMHAADz5s2rsw7hly7hGGetGyfVrE3JyckRf1LcvXs3Jk+erPWTs6mjMg4ZMgSrVq3CqVOnUFRUhG+//Ra9evXC48ePMWfOHI3+nYWrY7ru2WsqHh4e4t85OTl6l1O/0q/rXthnnnkG8fHx+Omnn1BUVITExEQMGzYMKpVKvJrdmOzt7fHiiy8C+CORVqlU4hedV155RWsd9auXTdVGy5Ytg5+fH+7du4eYmBitcuGe9oiICMTHx6NLly4at7AAph/T5j5OheNHSECagr7E01DfyQ1hYWGhccvA9evXdS5n6FYd9S/+6uerKe3UoUMHALW/yJirX/z6EmJS72u6MVlbW2POnDkA/rgFZMeOHSgvL4enpycmTJhQZx3CMd0anhdgdeOkmrUp6klinz59dC6TmJgo2fYUCgUmTJiAr776CkDtT4DqD4sJo2wdOnTIqJ9rG0OnTp3ELxqGhg8W9pObm5v487M+VlZWGDlyJA4dOgS5XA4iqtd+Fq5UNfRKq0C4vSMxMRF5eXlITEzEnTt3YGVlhWnTpmkt37NnTzg6OgLQfiCzsVhbW+Pdd98FUHtVOiMjQ6NcOKb1Hc+lpaU4f/683vqFBNzQvjX3cSr8QvDkABqtlfrogvpuedH1QO2TZa6urhrnnint9NxzzwGo/aL5448/1mtdcxFiOnbsmGS3T6h/4TTm/WTevHmwsLDAqVOn8Ntvv4nJdXh4uMFnHIDaZ3eEgZd0PXTKWh9Oqlmbov5Eu64rpQ8fPsSKFSvqXW91dTVqamr0lgv31QEQ72sGgMjISMhkMhQVFeHtt982uI2qqqpGSbxlMhnCwsIAABs3btR5lfP27dvYuHEjAGgloxUVFXrrlsvl4utX3w91ERLboqIio9fRZdSoUXjqqaegUqnw5Zdfilesx4wZo3HFT2BlZSVeqfr888/r7D3DXFdaZ86cCR8fH6hUKq1eEIRjWt+V//fffx8PHz7UW7cx+9bcx+mwYcMA1F4lbaqrklK4cuWKUQ83f/HFF+Lf+r4M7d+/X+dV7IKCAvHcE85TgSnt1KVLF7Edli1b1uQPFwO1DwdbWlri/v37iI2NlaRO4XgHjHs/8fHxER/cnD9/Pi5fvgyZTCbeK29IWloaampqYGVlxcOUtxGcVLM2xd/fH97e3gBqu0JS7/7s7NmzGD58eIPu68zNzUXXrl2xYsUKXLx4Uey5AQB++eUXcShwpVIpfnABQGBgIBYvXgwA2LBhA6ZMmYL09HTxCopKpcKlS5fw/vvvw8/PT+/9l1JbtmwZnJ2d8eDBA4waNUq8ZQYATp8+jVGjRqGoqAiurq74+9//rrGuj48Pli5dinPnzmkk2L///jtmzJiBR48ewcLCAqGhoUbH07NnTwC1Xd+Z8rCmhYWFOAz21q1b8c033wDQfeuHICYmBn5+fqiursaYMWOwdu1ajYcWi4uLcfjwYcyePRtDhw5tcGyGWFlZiUnSnj17cPXqVbFszJgxAGp/nt60aRMqKysB1N7yERUVhYSEBIP3cwr79sCBA3qPfXMfpz169BC/1Bi6qg7UJpXqk6C0tFRjvinHSUOlpKSgc+fOCAsLw/79+zW6lRR+pZowYQIOHjwIAJg8ebLeh/AUCgXGjBmDxMREcT+npqZi1KhRKCgogIODg9a5Z2o7ffTRR1AoFMjMzMTgwYNx+PBhsSvSR48e4fz585g/f76kv+YZ0qVLF/G4T0hIQEREBDIzM8Xy/Px87N27V7ytyxjdunUTH+DdsmWLUVerhe71Tpw4AaD2AcW6fp0D/jiWg4KCNH6dYK2YyT1dM9bE6jui4v/8z/+QlZWVuI6dnZ045K2dnR0lJibqHWxE36AC6vPxn0EfXF1dxRG38J/BHPbv368VT3V1tTjQgDApFApyc3PTiBOAxsiGxjBmREV9UlJSNIbiViqVGsOUOzs704kTJ7TWU49XGKJcGKUNqB1G+7/+67+01jM0CIkw3C/+M+pex44dycfHhwYPHiwuY2jAB3WXL1/WiNHJyanOUfxu3rwpDpKj/vqFAXCEqUuXLgbr0cWYYcqJiB4/fiwOWz158mRxfmFhIT399NMa+1x9mPLXXnuNZs+eTQBo9uzZWvUeP35cXNbS0pI6dOhAPj4+WoN1mPM4JfpjJMDp06cbXE59O4YmXQORmNuGDRu04lAoFBpDYwvT888/T8XFxXpf39atW8X2trOz0ximXC6X0/fff68zBlPb6ciRIxrnvbW1tVb8xgxTLjB1RMXq6mpauHChxvbt7e0bNEy5QBj1Vdi33t7e5OPjQ9HR0TrjU6lUYoyA/hEUnzRo0CACGjbSKmuZOKlmLV59k2oiojNnztC4cePI2dmZbGxsyNvbm8LDw+natWtEpH8EP31v1pWVlfTdd99RVFQUDRw4kLy8vMjGxobs7OzI39+fFi5cWOdoahcuXKB58+ZR9+7dSalUkpWVFbVr144GDx5McXFxlJ6ebvTrE5iSVBMR3blzh6Kjo6lHjx5ka2tLdnZ21KNHD3rrrbd0jrRIRHT06FFaunQpDR06lHx8fEihUJBCoaAuXbpQeHg4paWl6VyvrpH9duzYQUOGDCEnJydxlDX1D2pjk2oiosDAQHHZyMhIY3YFVVVV0RdffEHjx4+nDh06kLW1NSkUCurUqRO9+OKLtG3bNsrPzzeqLnXGJtVERAkJCeIXE/Xj4cGDB7R48WLy9fUla2trcnd3p5CQENq9ezcRkcGkmojohx9+oFGjRpGrq6u4b/WdT+Y4TomIrl69Kn55Ky0t1btcc06qiYguXbpEq1atookTJ1KXLl1IqVSShYUFOTg4kL+/P82aNYt++OEHveurv/fcuXOHFi5cSD4+PmRjY0MeHh40bdo0nSMtPsmUdrp37x6988471KdPH3J0dCSFQkG+vr4UGhpKGzdu1PoyYM6kWnDq1CmaMWMGeXt7k1wuJ2dnZwoICKC5c+dqjYJa13tBeXk5xcXFUc+ePTWSc33nBxFRVFQUASBPT0+DIygKbt68SQDI1taWHjx4UOfyrHWQEZn45A9jjDEmgREjRiA5ORmff/65Vp/hbYXwUG5ycrI4YBFrer1798bly5exdOlSfPDBB3Uu/9577yE2Nhbh4eHiqKys9eOkmjHGWLNw9uxZPPfccwgICBAfCGtrOKluflJSUhASEgILCwvcuHEDvr6+BpcvKyuDr68vHj58iOvXrzfZ4DWs8fGDiowxxpqFQYMGYfLkyfj111/FwTYYa0r37t0TH/6cPHlynQk1AHzyyScoKCjAokWLOKFuY3iYcsYYY83G6tWrERAQIPY6wVhTmDp1Kk6fPo28vDxUV1fDwcEBK1euNGpdpVKJuLg4MRlnbQff/sEYY4w1E3z7R/MwfPhwHD9+HE5OTujfvz9WrVqFoKCgpg6LNXOcVDPGGGOMMWYivqeaMcYYY4wxE3FSzRhjjDHGmIk4qWaMMcYYY8xEnFQzxhhjjDFmIk6qGWOMMcYYMxEn1YwxxhhjjJmIk2rGGGOMMcZMxEk1Y4wxxhhjJuKkmjHGGGOMMRP9P4q6/u1sg4e+AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Area Under the ROC Curve (AUC): 0.9389\n"
     ]
    }
   ],
   "source": [
    "# Use sen_spec_svm to draw ROC curve\n",
    "fig, ax = plt.subplots(figsize=(8, 6))\n",
    "ax.plot(1 - sen_spec_svm[:, 1], sen_spec_svm[:, 0], marker='.', color='tab:red', label='SVM Model')\n",
    "ax.plot([0, 1], [0, 1], linestyle='--', color='gray', label='Random Classifier')\n",
    "ax.set_xlabel('False Positive Rate (1 - Specificity)', fontsize=label_size)\n",
    "ax.set_ylabel('True Positive Rate (Sensitivity)', fontsize=label_size)\n",
    "ax.tick_params(axis='both', which='major', labelsize=ticklabel_size)\n",
    "\n",
    "# Set axis limits\n",
    "ax.set_xlim([-0.01, 1.00])\n",
    "ax.set_ylim([-0.01, 1.01])\n",
    "\n",
    "# Save the figure\n",
    "plt.savefig('ROC_Curve.png', dpi=300)\n",
    "\n",
    "# Add surface\n",
    "ax.fill_between(1 - sen_spec_svm[:, 1], sen_spec_svm[:, 0], color='tab:blue', alpha=0.2)\n",
    "\n",
    "plt.savefig('AUC.png', dpi=300)\n",
    "plt.show()\n",
    "\n",
    "# Calculate AUC\n",
    "from sklearn.metrics import auc\n",
    "roc_auc = auc(1 - sen_spec_svm[:, 1], sen_spec_svm[:, 0])\n",
    "print(f\"Area Under the ROC Curve (AUC): {roc_auc:.4f}\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "authorship_tag": "ABX9TyO5gS9/MePw+FDiXJA07L6y",
   "include_colab_link": true,
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
